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1.
Epidemiol Prev ; 47(3): 125-136, 2023.
Article in Italian | MEDLINE | ID: mdl-37154300

ABSTRACT

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.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Aged , Incidence , Nitrogen Dioxide/adverse effects , Environmental Exposure/adverse effects , Environmental Exposure/analysis , COVID-19/epidemiology , SARS-CoV-2 , Italy/epidemiology , Air Pollution/adverse effects , Air Pollution/analysis , Air Pollutants/adverse effects , Air Pollutants/analysis , Particulate Matter/adverse effects , Particulate Matter/analysis
2.
Environ Health Perspect ; 131(5): 57004, 2023 05.
Article in English | MEDLINE | ID: mdl-37167483

ABSTRACT

BACKGROUND: The role of chronic exposure to ambient air pollutants in increasing COVID-19 fatality is still unclear. OBJECTIVES: The study aimed to investigate the association between long-term exposure to air pollutants and mortality among 4 million COVID-19 cases in Italy. METHODS: We obtained individual records of all COVID-19 cases identified in Italy from February 2020 to June 2021. We assigned 2016-2019 mean concentrations of particulate matter (PM) with aerodynamic diameter ≤10µm (PM10), PM with aerodynamic diameter ≤2.5µm (PM2.5), and nitrogen dioxide (NO2) to each municipality (n=7,800) as estimates of chronic exposures. We applied a principal component analysis (PCA) and a generalized propensity score (GPS) approach to an extensive list of area-level covariates to account for major determinants of the spatial distribution of COVID-19 case-fatality rates. Then, we applied generalized negative binomial models matched on GPS, age, sex, province, and month. As additional analyses, we fit separate models by pandemic periods, age, and sex; we quantified the numbers of COVID-19 deaths attributable to exceedances in annual air pollutant concentrations above predefined thresholds; and we explored associations between air pollution and alternative outcomes of COVID-19 severity, namely hospitalizations or accesses to intensive care units. RESULTS: We analyzed 3,995,202 COVID-19 cases, which generated 124,346 deaths. Overall, case-fatality rates increased by 0.7% [95% confidence interval (CI): 0.5%, 0.9%], 0.3% (95% CI: 0.2%, 0.5%), and 0.6% (95% CI: 0.5%, 0.8%) per 1 µg/m3 increment in PM2.5, PM10, and NO2, respectively. Associations were higher among elderly subjects and during the first (February 2020-June 2020) and the third (December 2020-June 2021) pandemic waves. We estimated ∼8% COVID-19 deaths were attributable to pollutant levels above the World Health Organization 2021 air quality guidelines. DISCUSSION: We found suggestive evidence of an association between long-term exposure to ambient air pollutants with mortality among 4 million COVID-19 cases in Italy. https://doi.org/10.1289/EHP11882.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Humans , Aged , Air Pollution/analysis , Air Pollutants/analysis , Particulate Matter/analysis , Nitrogen Dioxide/analysis , Environmental Exposure/analysis
3.
JAAD Int ; 11: 72-77, 2023 Jun.
Article in English | MEDLINE | ID: mdl-36937029

ABSTRACT

Background: The magnitude of short/medium-term air pollution exposure on atopic dermatitis (AD) flare has not been fully investigated. The aim of the study was to investigate the association of short/medium-term exposure to airborne pollution on AD flares in patients treated with dupilumab. Methods: Observational case-crossover study. Patients with moderate-to-severe AD under treatment with dupilumab were included. The exposure of interest was the mean concentrations of coarse and fine particulate matter (PM10, PM2.5), nitrogen dioxide, and oxides (NO2, NOx). Different intervals were considered at 1 to 60 days before the AD flare and control visit, defined as the visit with the highest Eczema Area and Severity Index scores >8 and ≤7, respectively. A conditional logistic regression analysis adjusted for systemic treatments was employed to estimate the incremental odds (%) of flare every 10 µg/m3 pollutant concentration. Results: Data on 169 of 528 patients with AD having 1130 follow-up visits and 5840 air pollutant concentration measurements were retrieved. The mean age was 41.4 ± 20.3 years; 94 (55%) men. The incremental odds curve indicated a significant positive trend of AD flare for all pollutants in all time windows. At 60 days, every 10 µg/m3 PM10, PM2.5, NOx, and NO2 increase concentration was associated with 82%, 67%, 28%, and 113% odds of flare, respectively. Conclusions: In patients treated with dupilumab, acute air pollution exposure is associated with an increased risk for AD flare with a dose-response relationship.

5.
Environmetrics ; 33(4): e2723, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35574514

ABSTRACT

When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify-in space and time-the effectiveness of the adopted strategy. The lockdown measures taken worldwide in 2020 to reduce the spread of the SARS-CoV-2 virus can be envisioned as a policy intervention with an indirect effect on air quality. In this paper we propose a statistical spatiotemporal model as a tool for intervention analysis, able to take into account the effect of weather and other confounding factor, as well as the spatial and temporal correlation existing in the data. In particular, we focus here on the 2019/2020 relative change in nitrogen dioxide (NO 2 ) concentrations in the north of Italy, for the period of March and April during which the lockdown measure was in force. We found that during March and April 2020 most of the studied area is characterized by negative relative changes (median values around - 25%), with the exception of the first week of March and the fourth week of April (median values around 5%). As these changes cannot be attributed to a weather effect, it is likely that they are a byproduct of the lockdown measures. There are two aspects of our research that are equally interesting. First, we provide a unique statistical perspective for calculating the relative change in the NO 2 by jointly modeling pollutant concentrations time series. Second, as an output we provide a collection of weekly continuous maps, describing the spatial pattern of the NO 2 2019/2020 relative changes.

6.
RMD Open ; 8(1)2022 02.
Article in English | MEDLINE | ID: mdl-35292563

ABSTRACT

OBJECTIVE: Environmental air pollution has been associated with disruption of the immune system at a molecular level. The primary aim of the present study was to describe the association between long-term exposure to air pollution and risk of developing immune-mediated conditions. METHODS: We conducted a retrospective observational study on a nationwide dataset of women and men. Diagnoses of various immune-mediated diseases (IMIDs) were retrieved. Data on the monitoring of particulate matter (PM)10 and PM2.5 concentrations were retrieved from the Italian Institute of Environmental Protection and Research. Generalised linear models were employed to determine the relationship between autoimmune diseases prevalence and PM. RESULTS: 81 363 subjects were included in the study. We found a positive association between PM10 and the risk of autoimmune diseases (ρ+0.007, p 0.014). Every 10 µg/m3 increase in PM10 concentration was associated with an incremental 7% risk of having autoimmune disease. Exposure to PM10 above 30 µg/m3 and PM2.5 above 20 µg/m3 was associated with a 12% and 13% higher risk of autoimmune disease, respectively (adjusted OR (aOR) 1.12, 95% CI 1.05 to 1.20, and aOR 1.13, 95% CI 1.06 to 1.20). Exposure to PM10 was associated with an increased risk of rheumatoid arthritis; exposure to PM2.5 was associated with an increased risk of rheumatoid arthritis, connective tissue diseases (CTDs) and inflammatory bowel diseases (IBD). CONCLUSION: Long-term exposure to air pollution was associated with higher risk of developing autoimmune diseases, in particular rheumatoid arthritis, CTDs and IBD. Chronic exposure to levels above the threshold for human protection was associated with a 10% higher risk of developing IMIDs.


Subject(s)
Air Pollutants , Air Pollution , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Cohort Studies , Environmental Exposure/adverse effects , Environmental Exposure/analysis , Female , Humans , Male , Particulate Matter/adverse effects , Particulate Matter/analysis
7.
Epidemiol Prev ; 44(5-6 Suppl 2): 161-168, 2020.
Article in Italian | MEDLINE | ID: mdl-33412807

ABSTRACT

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.


Subject(s)
Air Microbiology , Air Pollutants/analysis , Air Pollution/adverse effects , COVID-19/epidemiology , Environmental Exposure , Models, Theoretical , Pandemics , SARS-CoV-2/isolation & purification , Air Pollutants/adverse effects , Air Pollution/statistics & numerical data , Environmental Monitoring , Geography, Medical , Global Burden of Disease , Humans , Italy/epidemiology , Machine Learning , Particulate Matter/adverse effects , Particulate Matter/analysis
8.
Epidemiol Prev ; 42(1): 46-59, 2018.
Article in Italian | MEDLINE | ID: mdl-29506361

ABSTRACT

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.


Subject(s)
Big Data , Ecology/methods , Epidemiologic Methods , Aerosols , Cities , Climate , Dust , Environmental Exposure/analysis , Farms , Forests , Fresh Water , Geographic Information Systems , Housing , Humans , Italy , Meteorological Concepts , Natural Resources , Particulate Matter/analysis , Plant Dispersal
9.
Environ Health Perspect ; 125(6): 067019, 2017 06 28.
Article in English | MEDLINE | ID: mdl-28657539

ABSTRACT

OBJECTIVES: The association between short-term air pollution exposure and daily mortality has been widely investigated, but little is known about the temporal variability of the effect estimates. We examined the temporal relationship between exposure to particulate matter (PM) (PM10, PM2.5) and gases (NO2, SO2, and CO) with mortality in a large metropolitan area over the last 17 y. METHODS: Our analysis included 359,447 nonaccidental deaths among ≥35-y-old individuals in Rome, Italy, over the study period 1998­2014. We related daily concentrations to mortality counts with a time-series Poisson regression analysis adjusted for long-term trends, meteorology, and population dynamics. RESULTS: Annual average concentrations decreased over the study period for all pollutants (e.g., from 42.9 to 26.6 µg/m3 for PM10). Each pollutant was positively associated with mortality, with estimated percentage increases over the entire study period ranging from 0.19% (95% CI: 0.13, 0.26) for a 1-Mg/m3 increase in CO (0­1 d lag) to 3.03% (95% CI: 2.44, 3.63) for a 10-µg/m3 increase in NO2 (0­5 d lag). We did not observe clear temporal patterns in year- or period-specific effect estimates for any pollutant. For example, we estimated that a 10-µg/m3 increase in PM10 was associated with 1.16% (95% CI: 0.53, 1.79), 0.99% (95% CI: 0.23, 1.77), and 1.87% (95% CI: 1.00, 2.74) increases in mortality for the periods 2001­2005, 2006­2010, and 2011­2014, respectively, and corresponding estimates for a 10-µg/m3 increase in NO2 were 4.20% (95% CI: 3.15, 5.25), 1.78% (95% CI: 0.73, 2.85), and 3.32% (95% CI: 2.03, 4.63). CONCLUSIONS: Mean concentrations of air pollutants have decreased over the last two decades in Rome, but effect estimates for a fixed increment in each exposure were generally consistent. These findings suggest that there has been little or no change in the overall toxicity of the air pollution mixture over time. https://doi.org/10.1289/EHP19.


Subject(s)
Air Pollution/statistics & numerical data , Environmental Exposure/statistics & numerical data , Adult , Air Pollutants/analysis , Air Pollutants/toxicity , Cardiovascular Diseases/mortality , Female , Humans , Italy , Male , Mortality , Particulate Matter/analysis , Particulate Matter/toxicity
11.
Environ Int ; 99: 234-244, 2017 Feb.
Article in English | MEDLINE | ID: mdl-28017360

ABSTRACT

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10 measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10 levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Environmental Exposure , Environmental Monitoring/methods , Particulate Matter/analysis , Humans , Italy , Meteorological Concepts , Rural Population , Seasons , Spacecraft , Urban Population
12.
Epidemiology ; 28(2): 172-180, 2017 03.
Article in English | MEDLINE | ID: mdl-27922535

ABSTRACT

BACKGROUND: Epidemiologic evidence on the association between short-term exposure to ultrafine particles and mortality is weak, due to the lack of routine measurements of these particles and standardized multicenter studies. We investigated the relationship between ultrafine particles and particulate matter (PM) and daily mortality in eight European urban areas. METHODS: We collected daily data on nonaccidental and cardiorespiratory mortality, particle number concentrations (as proxy for ultrafine particle number concentration), fine and coarse PM, gases and meteorologic parameters in eight urban areas of Finland, Sweden, Denmark, Germany, Italy, Spain, and Greece, between 1999 and 2013. We applied city-specific time-series Poisson regression models and pooled them with random-effects meta-analysis. RESULTS: We estimated a weak, delayed association between particle number concentration and nonaccidental mortality, with mortality increasing by approximately 0.35% per 10,000 particles/cm increases in particle number concentration occurring 5 to 7 days before death. A similar pattern was found for cause-specific mortality. Estimates decreased after adjustment for fine particles (PM2.5) or nitrogen dioxide (NO2). The stronger association found between particle number concentration and mortality in the warmer season (1.14% increase) became null after adjustment for other pollutants. CONCLUSIONS: We found weak evidence of an association between daily ultrafine particles and mortality. Further studies are required with standardized protocols for ultrafine particle data collection in multiple European cities over extended study periods.


Subject(s)
Air Pollution/statistics & numerical data , Cities , Environmental Exposure/statistics & numerical data , Mortality , Nitrogen Dioxide , Particulate Matter , Urban Population/statistics & numerical data , Adolescent , Adult , Aged , Child , Child, Preschool , Denmark , Europe , Female , Finland , Germany , Greece , Humans , Infant , Infant, Newborn , Italy , Male , Middle Aged , Poisson Distribution , Regression Analysis , Spain , Sweden , Time Factors , Young Adult
13.
Eur Respir J ; 48(3): 674-82, 2016 09.
Article in English | MEDLINE | ID: mdl-27338189

ABSTRACT

Epidemiological evidence on the associations between exposure to ultrafine particles (UFP), with aerodynamic electrical mobility diameters <100 nm, and health is limited. We gathered data on UFP from five European cities within 2001-2011 to investigate associations between short-term changes in concentrations and respiratory hospitalisations.We applied city-specific Poisson regression models and combined city-specific estimates to obtain pooled estimates. We evaluated the sensitivity of our findings to co-pollutant adjustment and investigated effect modification patterns by period of the year, age at admission and specific diagnoses.Our results for the whole time period do not support an association between UFP and respiratory hospitalisations, although we found suggestive associations among those 0-14 years old. We nevertheless report consistent adverse effect estimates during the warm period of the year, statistically significant after lag 2 when an increase by 10 000 particles per cm(3) was associated with a 4.27% (95% CI 1.68-6.92%) increase in hospitalisations. These effect estimates were robust to particles' mass or gaseous pollutants adjustment.Considering that our findings during the warm period may reflect better exposure assessment and that the main source of non-soluble UFP in urban areas is traffic, our results call for improved regulation of traffic emissions.


Subject(s)
Air Pollution/adverse effects , Environmental Exposure/adverse effects , Hospitalization/statistics & numerical data , Particulate Matter/adverse effects , Adolescent , Adult , Aged , Child , Child, Preschool , Environmental Monitoring , Europe , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Particle Size , Poisson Distribution , Pulmonary Medicine , Regression Analysis , Temperature , Young Adult
14.
Epidemiol Prev ; 38(3-4): 254-61, 2014.
Article in Italian | MEDLINE | ID: mdl-25115478

ABSTRACT

This work reviewed existing literature on airport related activities that could worsen surrounding air quality; its aim is to underline the progress coming from recent-year studies, the knowledge emerging from new approaches, the development of semi-empiric analytical methods as well as the questions still needing to be clarified. To estimate pollution levels, spatial and temporal variability, and the sources relative contributions integrated assessment, using both fixed point measurement and model outputs, are needed. The general picture emerging from the studies was a non-negligible and highly spatially variable (within 2-3 km from the fence line) airport contribution; even if it is often not dominant compared to other concomitant pollution sources. Results were highly airport-specific. Traffic volumes, landscape and meteorology were the key variables that drove the impacts. Results were thus hardly exportable to other contexts. Airport related pollutant sources were found to be characterized by unusual emission patterns (particularly ultrafine particles, black carbon and nitrogen oxides during take-off); high time-resolution measurements allow to depict the rapidly changing take-off effect on air quality that could not be adequately observed otherwise. Few studies used high time resolution data in a successful way as statistical models inputs to estimate the aircraft take-off contribution to the observed average levels. These findings should not be neglected when exposure of people living near airports is to be assessed.


Subject(s)
Air Pollutants , Air Pollution , Airports , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/adverse effects , Air Pollution/analysis , Health Impact Assessment , Humans , Models, Theoretical , Spatio-Temporal Analysis
15.
Epidemiol Prev ; 38(3-4): 244-53, 2014.
Article in Italian | MEDLINE | ID: mdl-25115477

ABSTRACT

OBJECTIVES: to assess air pollution spatial and temporal variability in the urban area nearby the Ciampino International Airport (Rome) and to investigate the airport-related emissions contribute. DESIGN AND SETTING: the study domain was a 64 km2 area around the airport. Two fifteen-day monitoring campaigns (late spring, winter) were carried out. Results were evaluated using several runs outputs of an airport-related sources Lagrangian particle model and a photochemical model (the Flexible Air quality Regional Model, FARM). MAIN OUTCOME MEASURES: both standard and high time resolution air pollutant concentrations measurements: CO, NO, NO2, C6H6, mass and number concentration of several PM fractions. 46 fixed points (spread over the study area) of NO2 and volatile organic compounds concentrations (fifteen days averages); deterministic models outputs. RESULTS: standard time resolution measurements, as well as model outputs, showed the airport contribution to air pollution levels being little compared to the main source in the area (i.e. vehicular traffic). However, using high time resolution measurements, peaks of particles associated with aircraft takeoff (total number concentration and soot mass concentration), and landing (coarse mass concentration) were observed, when the site measurement was downwind to the runway. CONCLUSIONS: the frequently observed transient spikes associated with aircraft movements could lead to a not negligible contribute to ultrafine, soot and coarse particles exposure of people living around the airport. Such contribute and its spatial and temporal variability should be investigated when assessing the airports air quality impact.


Subject(s)
Air Pollutants/analysis , Air Pollution/analysis , Airports , Rome , Urban Health
16.
Epidemiol Prev ; 37(4-5): 209-19, 2013.
Article in Italian | MEDLINE | ID: mdl-24293486

ABSTRACT

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.


Subject(s)
Air Pollution/analysis , Environmental Monitoring , Epidemiological Monitoring , Air Pollutants/analysis , Humans , Italy , Nitrogen Dioxide/analysis , Ozone/analysis , Particulate Matter/analysis , Urban Health
17.
Occup Environ Med ; 69(2): 133-9, 2012 Feb.
Article in English | MEDLINE | ID: mdl-21821870

ABSTRACT

OBJECTIVES: Few studies have assessed the effects of policies aimed to reduce traffic-related air pollution. The aims of this study were to evaluate the impact, in terms of air quality and health effects, of two low-emission zones established in Rome in the period 2001-2005 and to assess the impact by socioeconomic position (SEP) of the population. METHODS: We evaluated the effects of the intervention on various stages in the full-chain model, that is, pressure (number and age distribution of cars), emissions, PM(10) and NO(2) concentrations, population exposure and years of life gained (YLG). The impact was evaluated according to a small-area indicator of SEP. RESULTS: During the period 2001-2005, there was a decrease in the total number of cars (-3.8%), NO(2) and PM(10) emissions and concentrations (from 22.9 to 17.4 µg/m(3) for NO(2) and from 7.8 to 6.2 µg/m(3) for PM(10)), and in the residents' exposure. In the two low-emission zones, there was an additional decrease in air pollution concentrations (NO(2): -4.13 and -2.99 µg/m(3); PM(10): -0.70 and -0.47 µg/m(3)). As a result of the policy, 264 522 residents living along busy roads gained 3.4 days per person (921 YLG per 100,000) for NO(2) reduction. The gain was larger for people in the highest SEP group (1387 YLG per 100,000) than for residents in the lowest SEP group (340 YLG per 100,000). CONCLUSION: The traffic policy in Rome was effective in reducing traffic-related air pollution, but most of the health gains were found in well-off residents.


Subject(s)
Air Pollutants , Air Pollution/legislation & jurisprudence , Automobiles/legislation & jurisprudence , Environmental Exposure/adverse effects , Environmental Policy/legislation & jurisprudence , Longevity , Vehicle Emissions/legislation & jurisprudence , Air Pollutants/adverse effects , Air Pollutants/analysis , Air Pollution/analysis , Environmental Exposure/legislation & jurisprudence , Humans , Nitrogen Dioxide/analysis , Particulate Matter/analysis , Rome , Social Class , Vehicle Emissions/analysis
18.
Ann Ist Super Sanita ; 46(3): 242-53, 2010.
Article in English | MEDLINE | ID: mdl-20847456

ABSTRACT

The main objective of this study was to asses the temporal variation (1999 trough 2008) of air quality in Rome, focusing on airborne concentration of selected pollutants (PM10 and PM2.5 mass concentration and particle number concentration, PNC, carbon monoxide, CO, nitrogen oxides, NO and NO2) used for health effects assessment in epidemiological analyses. Time series analysis using Seasonal Kendall test has been applied. A statistically significant decreasing trend was found for primary gaseous pollutants and total particle number concentrations. Moreover a decreasing trend was assessed for PM10, PM2.5 and NO2 measured at traffic oriented sites even if the estimated reduction was lower compared with NO, CO and PNC. The urban background PM10 and NO2 concentrations seem to be practically unchanged since 1999 as no statistically significant trends were found. All the pollutants show higher slope of the estimated trend line at traffic oriented sites compared with those observed at the urban background. Thus a reduction of the intra-city concentration variability throughout the years occurred.


Subject(s)
Air Pollutants, Occupational/analysis , Air Pollution/statistics & numerical data , Environmental Monitoring/statistics & numerical data , Air Pollutants/analysis , Algorithms , Particle Size , Particulate Matter , Rome , Seasons
19.
Epidemiology ; 21(3): 414-23, 2010 May.
Article in English | MEDLINE | ID: mdl-20386174

ABSTRACT

BACKGROUND: Little is known about the short-term effects of ultrafine particles. METHODS: We evaluated the effect of particulate matter with an aerodynamic diameter or=35 years hospitalized for acute coronary syndrome, heart failure, lower respiratory tract infections, and chronic obstructive pulmonary disease (COPD). Information was available for factors indicating vulnerability, such as age and previous admissions for COPD. Particulate matter data were collected daily at one central fixed monitor. A case-crossover analysis was performed using a time-stratified approach. We estimated percent increases in risk per 14 microg/m PM10, per 10 microg/m PM2.5, and per 9392 particles/mL. RESULTS: An immediate impact (lag 0) of PM2.5 on hospitalizations for acute coronary syndrome (2.3% [95% confidence interval = 0.5% to 4.2%]) and heart failure (2.4% [0.3% to 4.5%]) was found, whereas the effect on lower respiratory tract infections (2.8% [0.5% to 5.2%]) was delayed (lag 2). Particle number concentration showed an association only with admissions for heart failure (lag 0-5; 2.4% [0.2% to 4.7%]) and COPD (lag 0; 1.6% [0.0% to 3.2%]). The effects were generally stronger in the elderly and during winter. There was no clear effect modification with previous COPD. CONCLUSIONS: We found sizeable acute health effects of fine and ultrafine particles. Although differential reliability in exposure assessment, in particular of ultrafine particles, precludes a firm conclusion, the study indicates that particulate matter of different sizes tends to have diverse outcomes, with dissimilar latency between exposure and health response.


Subject(s)
Air Pollutants/adverse effects , Emergency Service, Hospital/statistics & numerical data , Heart Diseases/epidemiology , Patient Admission/trends , Pulmonary Disease, Chronic Obstructive/epidemiology , Respiratory Tract Infections/epidemiology , Adult , Aged , Humans , International Classification of Diseases , Italy , Middle Aged , Particle Size
20.
Tob Control ; 16(5): 312-7, 2007 Oct.
Article in English | MEDLINE | ID: mdl-17897989

ABSTRACT

BACKGROUND: A smoking ban in all indoor public places was enforced in Italy on 10 January 2005. METHODS: We compared indoor air quality before and after the smoking ban by monitoring the indoor concentrations of fine (<2.5 microm diameter, PM2.5) and ultrafine particulate matter (<0.1 microm diameter, UFP). PM2.5 and ultrafine particles were measured in 40 public places (14 bars, six fast food restaurants, eight restaurants, six game rooms, six pubs) in Rome, before and after the introduction of the law banning smoking (after 3 and 12 months). Measurements were taken using real time particle monitors (DustTRAK Mod. 8520 TSI; Ultra-fine Particles Counter-TRAK Model 8525 TSI). The PM2.5 data were scaled using a correction equation derived from a comparison with the reference method (gravimetric measurement). The study was completed by measuring urinary cotinine, and pre-law and post-law enforcement among non-smoking employees at these establishments RESULTS: In the post-law period, PM2.5 decreased significantly from a mean concentration of 119.3 microg/m3 to 38.2 microg/m3 after 3 months (p<0.005), and then to 43.3 microg/m3 a year later (p<0.01). The UFP concentrations also decreased significantly from 76,956 particles/cm3 to 38,079 particles/cm3 (p<0.0001) and then to 51,692 particles/cm3 (p<0.01). Similarly, the concentration of urinary cotinine among non-smoking workers decreased from 17.8 ng/ml to 5.5 ng/ml (p<0.0001) and then to 3.7 ng/ml (p<0.0001). CONCLUSION: The application of the smoking ban led to a considerable reduction in the exposure to indoor fine and ultrafine particles in hospitality venues, confirmed by a contemporaneous reduction of urinary cotinine.


Subject(s)
Air Pollution, Indoor/analysis , Environmental Exposure/analysis , Particulate Matter/analysis , Tobacco Smoke Pollution/analysis , Adult , Biomarkers/urine , Cotinine/urine , Environmental Monitoring/methods , Female , Humans , Italy , Male , Occupational Exposure/analysis , Public Facilities , Restaurants/legislation & jurisprudence , Smoking/legislation & jurisprudence , Smoking Prevention , Tobacco Smoke Pollution/legislation & jurisprudence , Tobacco Smoke Pollution/prevention & control
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