263 research outputs found
Pratiquer l’épidémiologie avec des communautés de pairs étendues
No full textBruna De Marchi, Pier Alberto Bertazzi, Annibale Biggeri. Pratiquer l’épidémiologie avec des communautés de pairs étendues. Gwenola Le Naour, Renaud Bécot. Vivre et lutter dans un monde toxique. Violence environnementale et santé à l'âge du pétrol
Pratiquer l’épidémiologie avec des communautés de pairs étendues
No full textBruna De Marchi, Pier Alberto Bertazzi, Annibale Biggeri. Pratiquer l’épidémiologie avec des communautés de pairs étendues. Gwenola Le Naour, Renaud Bécot. Vivre et lutter dans un monde toxique. Violence environnementale et santé à l'âge du pétrol
A Bayesian Kriging Model to Predict PM10 Annual Average Concentrations for the Lombardy Region (Italy)
No full textRecent literature on long-range spatial exposure assessment focused on Kriging or atmospheric pollution models. We develop a full Bayesian approach to Universal Kriging which allows appropriate treatment of prediction uncertainty
Specificità e uniformazione nell'attività di sorveglianza sanitaria
No full textL’attività di sorveglianza sanitaria effettuata per realtà industriali (o produttive) caratterizzate da una estrema diversificazione delle attività svolte e da una distribuzione su molteplici sedi, spesso allocate in differenti regioni, può rappresentare una sfida importante per l’attività del medico competente.
In tali situazioni, infatti, esiste la concreta possibilità che in assenza di un costante intervento di supervisione e coordinamento nonché per l’esistenza nelle diverse regioni di impianti normativi non uniformi nella trattazione degli aspetti inerenti l’attività di tutela di salute e sicurezza nei luoghi di lavoro, si possa determinare una disomogeneità nelle modalità con cui l’attività di sorveglianza viene strutturata ed applicata, talvolta anche in circostanze del tutto sovrapponibili.
Viene qui presentata l’esperienza condotta all’interno di un grande gruppo industriale presso il quale è stato portato a termine un importante lavoro di rivalutazione delle attività e dei rischi presenti, che ha consentito di razionalizzare ed omogeneizzare, su tutto il vasto ed articolato tessuto produttivo del Gruppo, l’attività dei medici competenti ed in particolare i contenuti e l’organizzazione della sorveglianza sanitaria
Temporal trends of PM10 and its impact on mortality in Lombardy, Italy
No full textIntroduction Exposure to particulate matter with diameter ≤10 μm (PM10) entails well documented adverse effects on human health. In the last decade, concentration of PM10 in Lombardy (10 million inhabitants), Italy, has been gradually decreasing. We evaluated how the mortality burden due to PM10 varied in that same period. Methods We focused on 13 areas of the Region in 2003–2014: 11 cities with more than 50,000 inhabitants, 1 smaller alpine town and 1 agricultural province. For each area, we collected PM10 annual average concentrations and natural mortality data, and we used the posterior area-specific effects from a previous Bayesian meta-analysis to estimate the short-term impact of PM10 on mortality, in terms of deaths attributable (AD) to annual average exposures exceeding the WHO threshold of 20 μg/m3. Results PM10 annual average values showed a non-homogenous decreasing trend in the investigated time period in most of the areas. Overall, the population-weighted exposure levels decreased, except for a peak in 2011, but never met the WHO threshold. In 2003–2006, PM10 levels were responsible, on average, for 343.0 annual AD from natural causes that decreased to 253.5 in 2007–2010 and to 208.3 in 2011–2014. Overall we estimated that PM10 was responsible for about 1% of all natural deaths (min-max range: 0.86%–1.42%); the impact was heterogeneous among areas. Conclusions By collecting routinely available data for the most populated areas in Lombardy, we returned a picture of air pollution and health trends in the last decade. Notwithstanding the observed reduction in PM10 between 2003 and 2014 and the resulting decline in the number of AD, the impact is still relevant. Hence, appropriate policies for emission reduction could have a further beneficial effect on population health. Studies based on routine data and local effect estimates are recommended to properly inform the policy-making process
Geostatistical integration and uncertainty in pollutant concentration surface under preferential sampling
No full textIn this paper the focus is on environmental statistics, with the aim of estimating the concentration surface and related uncertainty of an air pollutant. We used air quality data recorded by a network of monitoring stations within a Bayesian framework to overcome difficulties in accounting for prediction uncertainty and to integrate information provided by deterministic models based on emissions meteorology and chemico-physical characteristics of the atmosphere. Several authors have proposed such integration, but all the proposed approaches rely on representativeness and completeness of existing air pollution monitoring networks. We considered the situation in which the spatial process of interest and the sampling locations are not independent. This is known in the literature as the preferential sampling problem, which if ignored in the analysis, can bias geostatistical inferences. We developed a Bayesian geostatistical model to account for preferential sampling with the main interest in statistical integration and uncertainty. We used PM10 data arising from the air quality network of the Environmental Protection Agency of Lombardy Region (Italy) and numerical outputs from the deterministic model. We specified an inhomogeneous Poisson process for the sampling locations intensities and a shared spatial random component model for the dependence between the spatial location of monitors and the pollution surface. We found greater predicted standard deviation differences in areas not properly covered by the air quality network. In conclusion, in this context inferences on prediction uncertainty may be misleading when geostatistical modelling does not take into account preferential sampling
Engineered nanomaterials exposure in the production of graphene
No full textABSTRACT: The objective of this study was to obtain the multi-metric occupational exposure assessment to graphene family nanomaterials (GFNs) particles of workers engaged in the large-scale production of graphene. The study design consisted of the combination of (i) direct-reading instruments, used to evaluate the total particle number concentrations relative to the background concentration (time series with spatial approach) and the mean size-dependent characteristics of particles (mean diameter and surface-area concentration) and (ii) filter-based air sampling for the determination of size-resolved particle mass concentrations. The data obtained from direct reading measurement were then used to estimate the 8-h time weighted average (8-h TWA) exposure to GFNs particles for workers involved in different working tasks. Workers were generally exposed to 8-h TWA GFNs particle levels lower than the proposed reference value (40,000 particle/cm3). Furthermore, despite high short-term exposure conditions were present during specific operations of the production process, the possibility of significant exposure peaks is not likely to be expected. The estimated 8-h TWA concentration showed differences between the unexposed (<100 particle/cm3; <0.05 μg/m3) and exposed subjects (mean concentration ranging from 909 to 6438 particle/cm3 and from 0.38 to 3.86 μg/m3). The research outcomes can be of particular interest because the exposure of workers in real working conditions was assessed with a multi-metric approach; in this regard, the study suggests that workers who are directly involved in some specific working task (material sampling for quality control) have higher potential for occupational exposure than operators who are in charge of routine production work. © 2016 American Association for Aerosol Researc
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