[The peer-review process: critical issues and challenges from an online survey]. / Il processo della revisione tra pari: criticità e sfide emerse da una survey online.

BACKGROUND: the peer-review process, which is the foundation of modern scientific production, represents one of its essential elements. However, despite numerous benefits, it presents several critical issues. OBJECTIVES: to collect the opinions of a group of researchers from the epidemiological scientific community on peer-review processes. DESIGN: cross-sectional study using a questionnaire evaluation. SETTING AND PARTICIPANTS: a 29-question survey was administered to 516 healthcare professionals through the SurveyMonkey platform. The questions focused on the individual characteristics of the respondents and their perceived satisfaction with some characteristics of the review process as well as their propensity of changing some aspects of it. In addition, three open-ended questions were included, allowing respondents to provide comments on the role that reviewers and the review process should play. Descriptive statistics were produced in terms of absolute frequencies and percentages for the information collected through the questionnaire. Secondly, a multiple logistic regression analysis was conducted to assess the willingness to change certain aspects of peer review, adjusting for covariates such as age, sex, being the author of at least one scientific work, being a reviewer of at least one scientific work, and belonging to a specific discipline. The results are expressed as odds ratios (ORs) and their 95% confidence intervals (95%CI). Text analysis and representation using word cloud were also used for an open-ended question. MAIN OUTCOMES MEASURES: level of satisfaction regarding some characteristics of the peer-review process. RESULTS: a total of 516 participants completed the questionnaire. Specifically, 87.2% (N. 450) of the participants were the authors of at least one scientific publication, 78.7% were first authors at least once (N. 406), and 71.5% acted as reviewers within the peer-review process (N. 369). The results obtained from the multiple logistic regression models did not highlight any significant differences in terms of propensity to change for age and sex categories, except for a lower propensity of the under 35 age group towards unmasking, defined as the presence of reviewers and editorial boards names on the publish article (OR <35 years vs 45-54 years: 0.51; 95%CI 0.29-0.89) and a higher propensity for post-formatting proposals, defined as the possibility of formatting the article following journal guidelines after the acceptance, among those under 45 (OR <35 years vs 45-54 years: 1.73; 95%CI 0.90-3.31; OR 35-44 years vs 45-54 years: 2.02; 95%CI 1.10-3.72). Finally, approximately 50% of respondents found it appropriate to receive credits for the revision work performed, while approximately 30% found it appropriate to receive a discount on publication fees for the same journal in which they acted as reviewers. CONCLUSIONS: the peer-review process is considered essential, but imperfect, by the professionals who participated in the questionnaire, thus providing a clear picture of the value that peer-review adds rigorously to each scientific work and the need to continue constructive dialogue on this topic within the scientific community.

Association between short-term exposure to air pollutants and cause-specific daily mortality in Italy. A nationwide analysis.

BACKGROUND/AIM: Daily air pollution has been linked with mortality from urban studies. Associations in rural areas are still unclear and there is growing interest in testing the role that air pollution has on other causes of death. This study aims to evaluate the association between daily air pollution and cause-specific mortality in all 8092 Italian municipalities. METHODS: Natural, cardiovascular, cardiac, ischemic, cerebrovascular, respiratory, metabolic, diabetes, nervous and psychiatric causes of death occurred in Italy were extracted during 2013-2015. Daily ambient PM10, PM2.5 and NO2 concentrations were estimated through machine learning algorithms. The associations between air pollutants and cause-specific mortality were estimated with a time-series approach using a two-stage analytic protocol where area-specific over-dispersed Poisson regression models where fit in the first stage, followed by a meta-analysis in the second. We tested for effect modification by sex, age class and the degree of urbanisation of the municipality. RESULTS: We estimated a positive association between PM10 and PM2.5 and the mortality from natural, cardiovascular, cardiac, respiratory and nervous system causes, but not with metabolic or psychiatric causes of death. In particular, mortality from nervous diseases increased by 4.55% (95% CI: 2.51-6.63) and 9.64% (95% CI: 5.76-13.65) for increments of 10 µg/m3 in PM10 and PM2.5 (lag 0-5 days), respectively. NO2 was positively associated with respiratory (6.68% (95% CI: 1.04-12.62)) and metabolic (7.30% (95% CI: 1.03-13.95)) mortality for increments of 10 µg/m3 (lag 0-5). Higher associations with natural mortality were found among the elderly, while there were no differential effects between sex or between rural and urban areas. CONCLUSIONS: Short-term exposure to particulate matter was associated with mortality from nervous diseases. Mortality from metabolic diseases was associated with NO2 exposure. Other associations are confirmed and updated, including the contribution of lowly urbanised areas. Health effects were also found in suburban and rural areas.

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study.

BACKGROUND: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. METHODS: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. RESULTS: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. CONCLUSIONS: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Long-term effects of air pollutants on respiratory and cardiovascular mortality in a port city along the Adriatic sea.

BACKGROUND: Shipping and port-related air pollution has a significant health impact on a global scale. The present study aimed to assess the mortality burden attributable to long-term exposure to ambient particulate matter (PM2.5, PM10) and nitrogen dioxide (NO2) in the city of Ancona (Italy), with one of the leading national commercial harbours. METHODS: Exposure to air pollutants was derived by dispersion models. The relationship between the long-term exposure of air pollution exposure and cause-specific mortality was evaluated by Poisson regression models, after adjustment for gender, age and socioeconomic status. Results are expressed as percent change of risk (and relative 95% confidence intervals) per 5 unit increases in the exposures. The health impact on the annual number of premature cause-specific deaths was also assessed. RESULTS: PM2.5 and NO2 annual concentrations were higher in the area close to the harbour than in the rest of the city. Positive associations between each pollutant and most of the mortality outcomes were observed, with estimates of up to 7.6% (95%CI 0.1, 15.6%) for 10 µg/m3 increase in NO2 and cardiovascular mortality and 15.3% (95%CI-1.1, 37.2%) for 10 µg/m3 increase PM2.5 and lung cancer. In the subpopulation living close to the harbour, there were excess risks of up to 13.5%, 24.1% and 37.9% for natural, cardiovascular and respiratory mortality. The number of annual premature deaths due to the excess of PM2.5 and NO2 exposure (having as a reference the 2021 World Health Organization Air Quality Guidelines) was 82 and 25, respectively. CONCLUSIONS: Our study confirms the long-term health effects of PM and NO2 on mortality and reveals a higher mortality burden in areas close to shipping and port-related emissions. Estimating the source-specific health burdens is key to achieve a deeper understanding of the role of different emission sources, as well as to support effective and targeted mitigation strategies.

[Short-term effects of PM10 on cause-specific mortality and the role of long-term environmental pressures in the industrial areas of Brindisi and Civitavecchia]. / Effetti a breve termine del PM10 sulla mortalità causa-specifica e ruolo delle pressioni ambientali di lungo periodo nelle aree industriali di Brindisi e Civitavecchia.

OBJECTIVES: the health status of people living near industrial plants is often exposed to several environmental risk factors, including air pollution. The aim of this study is to assess the relationship between daily PM10 levels and cause-specific mortality in a selection of municipalities near two industrial plants from 2006 to 2015. DESIGN: a time-series design with Poisson regression adjusted for a predefined set of confounders was used to quantify the association between exposure, calculated as daily PM10 levels extrapolated from machine-learning models using satellite data, and cause-specific mortality. SETTING AND PARTICIPANTS: twenty municipalities near the thermal power plants in Civitavecchia and Brindisi were selected. The municipalities were then divided into three scenarios of chronic exposure derived from SPRAY simulation models of pollutant deposition. MAIN OUTCOME MEASURES: daily cause-specific non-accidental, cardiovascular, and respiratory deaths defined according to the International Classification of Diseases code at the municipality level. RESULTS: a total of 41,942 deaths were observed in the entire area (10,503 in the Civitavecchia area and 31,439 in the Brindisi area), of which approximately 41% were due to cardiovascular causes and 8% due to respiratory causes. The association showed an increase in shortterm effects in municipalities with higher chronic levels of pollution exposure. For example, risk estimates reported as percentage increases per 10-unit increase in PM10 were 6.7% (95% CI 0.9, 12.7%) in scenario 3 (highest exposure) compared to 4.2% (-1.2, 9.9%) and 2.7% (-4.2, 10.2%) in scenarios 2 and 1, respectively, in the area near the Civitavecchia plant. Similar effects were observed for the Brindisi area. CONCLUSIONS: despite the well-documented relationship between short-term pollution and mortality, it appears that greater chronic exposure to industrial pollutants leads to increased short-term effects of PM10. The limited number of events suggests that this study could serve as a starting point for a larger investigation.

[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.

Long-term exposure to air pollution and risk of venous thromboembolism in a large administrative cohort.

BACKGROUND: Venous thromboembolisms (VTE) are one of the most frequent cause among the cardiovascular diseases. Despite the association between long-term exposure to air pollution and cardiovascular outcomes have been widely explored in epidemiological literature, little is known about the air pollution related effects on VTE. We aimed to evaluate this association in a large administrative cohort in 15 years of follow-up. METHODS: Air pollution exposure (NO2, PM10 and PM2.5) was derived by land use regression models obtained by the ESCAPE framework. Administrative health databases were used to identify VTE cases. To estimate the association between air pollutant exposures and risk of hospitalizations for VTE (in total and divided in deep vein thrombosis (DVT) and pulmonary embolism (PE)), we used Cox regression models, considering individual, environmental (noise and green areas), and contextual characteristics. Finally, we considered potential effect modification for individual covariates and previous comorbidities. RESULTS: We identified 1,954 prevalent cases at baseline and 20,304 cases during the follow-up period. We found positive associations between PM2.5 exposures and DVT, PE and VTE with hazard ratios (HRs) up to 1.082 (95% confidence intervals: 0.992, 1.181), 1.136 (0.994, 1.298) and 1.074 (0.996, 1.158) respectively for 10 µg/m3 increases. The association was stronger in younger subjects (< 70 years old compared to > 70 years old) and among those who had cancer. CONCLUSION: The effect of pollutants on PE and VTE hospitalizations, although marginally non-significant, should be interpreted as suggestive of a health effect that deserves attention in future studies.

Long-term exposure to air pollution and liver cancer incidence in six European cohorts.

Particulate matter air pollution and diesel engine exhaust have been classified as carcinogenic for lung cancer, yet few studies have explored associations with liver cancer. We used six European adult cohorts which were recruited between 1985 and 2005, pooled within the "Effects of low-level air pollution: A study in Europe" (ELAPSE) project, and followed for the incidence of liver cancer until 2011 to 2015. The annual average exposure to nitrogen dioxide (NO2 ), particulate matter with diameter <2.5 µm (PM2.5 ), black carbon (BC), warm-season ozone (O3 ), and eight elemental components of PM2.5 (copper, iron, zinc, sulfur, nickel, vanadium, silicon, and potassium) were estimated by European-wide hybrid land-use regression models at participants' residential addresses. We analyzed the association between air pollution and liver cancer incidence by Cox proportional hazards models adjusting for potential confounders. Of 330 064 cancer-free adults at baseline, 512 developed liver cancer during a mean follow-up of 18.1 years. We observed positive linear associations between NO2 (hazard ratio, 95% confidence interval: 1.17, 1.02-1.35 per 10 µg/m3 ), PM2.5 (1.12, 0.92-1.36 per 5 µg/m3 ), and BC (1.15, 1.00-1.33 per 0.5 10-5 /m) and liver cancer incidence. Associations with NO2 and BC persisted in two-pollutant models with PM2.5 . Most components of PM2.5 were associated with the risk of liver cancer, with the strongest associations for sulfur and vanadium, which were robust to adjustment for PM2.5 or NO2 . Our study suggests that ambient air pollution may increase the risk of liver cancer, even at concentrations below current EU standards.

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 µm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 µg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions.

Long-term exposure to fine particle elemental components and lung cancer incidence in the ELAPSE pooled cohort.

BACKGROUND: An association between long-term exposure to fine particulate matter (PM2.5) and lung cancer has been established in previous studies. PM2.5 is a complex mixture of chemical components from various sources and little is known about whether certain components contribute specifically to the associated lung cancer risk. The present study builds on recent findings from the "Effects of Low-level Air Pollution: A Study in Europe" (ELAPSE) collaboration and addresses the potential association between specific elemental components of PM2.5 and lung cancer incidence. METHODS: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM2.5 representing non-tail pipe emissions (copper (Cu), iron (Fe), and zinc (Zn)), long-range transport (sulfur (S)), oil burning/industry emissions (nickel (Ni), vanadium (V)), crustal material (silicon (Si)), and biomass burning (potassium (K)) to cohort participants' baseline residential address based on 100 m by 100 m grids from newly developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). RESULTS: The pooled study population comprised 306,550 individuals with 3916 incident lung cancer events during 5,541,672 person-years of follow-up. We observed a positive association between exposure to all eight components and lung cancer incidence, with adjusted HRs of 1.10 (95% CI 1.05, 1.16) per 50 ng/m3 PM2.5 K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m3 PM2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m3 PM2.5 S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m3 PM2.5 V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO2). After adjustment for PM2.5 mass, effect estimates of K, Ni, S, and V were slightly attenuated, whereas effect estimates of Cu, Si, Fe, and Zn became null or negative. CONCLUSIONS: Our results point towards an increased risk of lung cancer in connection with sources of combustion particles from oil and biomass burning and secondary inorganic aerosols rather than non-exhaust traffic emissions. Specific limit values or guidelines targeting these specific PM2.5 components may prove helpful in future lung cancer prevention strategies.

Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM2.5, BC, NO2, and O3: An Analysis of European Cohorts in the ELAPSE Project.

INTRODUCTION: Epidemiological cohort studies have consistently found associations between long-term exposure to outdoor air pollution and a range of morbidity and mortality endpoints. Recent evaluations by the World Health Organization and the Global Burden of Disease study have suggested that these associations may be nonlinear and may persist at very low concentrations. Studies conducted in North America in particular have suggested that associations with mortality persisted at concentrations of particulate matter with an aerodynamic diameter of less than 2.5 µm (PM2.5) well below current air quality standards and guidelines. The uncertainty about the shape of the concentration-response function at the low end of the concentration distribution, related to the scarcity of observations in the lowest range, was the basis of the current project. Previous studies have focused on PM2.5, but increasingly associations with nitrogen dioxide (NO2) are being reported, particularly in studies that accounted for the fine spatial scale variation of NO2. Very few studies have evaluated the effects of long-term exposure to low concentrations of ozone (O3). Health effects of black carbon (BC), representing primary combustion particles, have not been studied in most large cohort studies of PM2.5. Cohort studies assessing health effects of particle composition, including elements from nontailpipe traffic emissions (iron, copper, and zinc) and secondary aerosol (sulfur) have been few in number and reported inconsistent results. The overall objective of our study was to investigate the shape of the relationship between long-term exposure to four pollutants (PM2.5, NO2, BC, and O3) and four broad health effect categories using a number of different methods to characterize the concentration-response function (i.e., linear, nonlinear, or threshold). The four health effect categories were (1) natural- and cause-specific mortality including cardiovascular and nonmalignant as well as malignant respiratory and diabetes mortality; and morbidity measured as (2) coronary and cerebrovascular events; (3) lung cancer incidence; and (4) asthma and chronic obstructive pulmonary disease (COPD) incidence. We additionally assessed health effects of PM2.5 composition, specifically the copper, iron, zinc, and sulfur content of PM2,5. METHODS: We focused on analyses of health effects of air pollutants at low concentrations, defined as less than current European Union (EU) Limit Values, U.S. Environmental Protection Agency (U.S. EPA), National Ambient Air Quality Standards (NAAQS), and/or World Health Organization (WHO) Air Quality Guideline values for PM2.5, NO2, and O3. We address the health effects at low air pollution levels by performing new analyses within selected cohorts of the ESCAPE study (European Study of Cohorts for Air Pollution Effects; Beelen et al. 2014a) and within seven very large European administrative cohorts. By combining well-characterized ESCAPE cohorts and large administrative cohorts in one study the strengths and weaknesses of each approach can be addressed. The large administrative cohorts are more representative of national or citywide populations, have higher statistical power, and can efficiently control for area-level confounders, but have fewer possibilities to control for individual-level confounders. The ESCAPE cohorts have detailed information on individual confounders, as well as country-specific information on area-level confounding. The data from the seven included ESCAPE cohorts and one additional non-ESCAPE cohort have been pooled and analyzed centrally. More than 300,000 adults were included in the pooled cohort from existing cohorts in Sweden, Denmark, Germany, the Netherlands, Austria, France, and Italy. Data from the administrative cohorts have been analyzed locally, without transfer to a central database. Privacy regulations prevented transfer of data from administrative cohorts to a central database. More than 28 million adults were included from national administrative cohorts in Belgium, Denmark, England, the Netherlands, Norway, and Switzerland as well as an administrative cohort in Rome, Italy. We developed central exposure assessment using Europewide hybrid land use regression (LUR) models, which incorporated European routine monitoring data for PM2.5, NO2, and O3, and ESCAPE monitoring data for BC and PM2.5 composition, land use, and traffic data supplemented with satellite observations and chemical transport model estimates. For all pollutants, we assessed exposure at a fine spatial scale, 100 × 100 m grids. These models have been applied to individual addresses of all cohorts including the administrative cohorts. In sensitivity analyses, we applied the PM2.5 models developed within the companion HEI-funded Canadian MAPLE study (Brauer et al. 2019) and O3 exposures on a larger spatial scale for comparison with previous studies. Identification of outcomes included linkage with mortality, cancer incidence, hospital discharge registries, and physician-based adjudication of cases. We analyzed natural-cause, cardiovascular, ischemic heart disease, stroke, diabetes, cardiometabolic, respiratory, and COPD mortality. We also analyzed lung cancer incidence, incidence of coronary and cerebrovascular events, and incidence of asthma and COPD (pooled cohort only). We applied the Cox proportional hazard model with increasing control for individual- and area-level covariates to analyze the associations between air pollution and mortality and/or morbidity for both the pooled cohort and the individual administrative cohorts. Age was used as the timescale because of evidence that this results in better adjustment for potential confounding by age. Censoring occurred at the time of the event of interest, death from other causes, emigration, loss to follow-up for other reasons, or at the end of follow-up, whichever came first. A priori we specified three confounder models, following the modeling methods of the ESCAPE study. Model 1 included only age (time axis), sex (as strata), and calendar year of enrollment. Model 2 added individual-level variables that were consistently available in the cohorts contributing to the pooled cohort or all variables available in the administrative cohorts, respectively. Model 3 further added area-level socioeconomic status (SES) variables. A priori model 3 was selected as the main model. All analyses in the pooled cohort were stratified by subcohort. All analyses in the administrative cohorts accounted for clustering of the data in neighborhoods by adjusting the variance of the effect estimates. The main exposure variable we analyzed was derived from the Europewide hybrid models based on 2010 monitoring data. Sensitivity analyses were conducted using earlier time periods, time-varying exposure analyses, local exposure models, and the PM2.5 models from the Canadian MAPLE project. We first specified linear single-pollutant models. Two-pollutant models were specified for all combinations of the four main pollutants. Two-pollutant models for particle composition were analyzed with PM2.5 and NO2 as the second pollutant. We then investigated the shape of the concentration-response function using natural splines with two, three, and four degrees of freedom; penalized splines with the degrees of freedom determined by the algorithm and shape-constrained health impact functions (SCHIF) using confounder model 3. Additionally, we specified linear models in subsets of the concentration range, defined by removing concentrations above a certain value from the analysis, such as for PM2.5 25 µg/m3 (EU limit value), 20, 15, 12 µg/m3 (U.S. EPA National Ambient Air Quality Standard), and 10 µg/m3 (WHO Air Quality Guideline value). Finally, threshold models were evaluated to investigate whether the associations persisted below specific concentration values. For PM2.5, we evaluated 10, 7.5, and 5 µg/m3 as potential thresholds. Performance of threshold models versus the corresponding no-threshold linear model were evaluated using the Akaike information criterion (AIC). RESULTS: In the pooled cohort, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values (25 µg/m3 and 40 µg/m3, respectively). More than 50,000 had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 µg/m3). More than 25,000 subjects had a residential PM2.5 exposure below the WHO guideline (10 µg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and diabetes mortality. In our main model, the hazard ratios (HRs) (95% [confidence interval] CI) were 1.13 (CI = 1.11, 1.16) for an increase of 5 µg/m3 PM2.5, 1.09 (CI = 1.07, 1.10) for an increase of 10 µg/m3 NO2, and 1.08 (CI = 1.06, 1.10) for an increase of 0.5 × 10-5/m BC for natural-cause mortality. The highest HRs were found for diabetes mortality. Associations with O3 were negative, both in the fine spatial scale of the main ELAPSE model and in large spatial scale exposure models. For PM2.5, NO2, and BC, we generally observed a supralinear association with steeper slopes at low exposures and no evidence of a concentration below which no association was found. Subset analyses further confirmed that these associations remained at low levels: below 10 µg/m3 for PM2.5 and 20 µg/m3 for NO2. HRs were similar to the full cohort HRs for subjects with exposures below the EU limit values for PM2.5 and NO2, the U.S. NAAQS values for PM2.5, and the WHO guidelines for PM2.5 and NO2. The mortality associations were robust to alternative specifications of exposure, including different time periods, PM2.5 from the MAPLE project, and estimates from the local ESCAPE model. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. HRs in two-pollutant models were attenuated but remained elevated and statistically significant forPM2.5 and NO2. In two-pollutant models of PM2.5 and NO2 HRs for natural-cause mortality were 1.08 (CI = 1.05, 1.11) for PM2.5 and 1.05 (CI = 1.03, 1.07) for NO2. Associations with O3 were attenuated but remained negative in two-pollutant models with NO2, BC, and PM2.5. We found significant positive associations between PM2.5, NO2, and BC and incidence of stroke and asthma and COPD hospital admissions. Furthermore, NO2 was significantly related to acute coronary heart disease and PM2.5 was significantly related to lung cancer incidence. We generally observed linear to supralinear associations with no evidence of a threshold, with the exception of the association between NO2 and acute coronary heart disease, which was sublinear. Subset analyses documented that associations remained even with PM2.5 below 20 µg/m3 and possibly 12 µg/m3. Associations remained even when NO2 was below 30 µg/m3 and in some cases 20 µg/m3. In two-pollutant models, NO2 was most consistently associated with acute coronary heart disease, stroke, asthma, and COPD hospital admissions. PM2.5 was not associated with these outcomes in two-pollutant models with NO2. PM2.5 was the only pollutant that was associated with lung cancer incidence in two-pollutant models. Associations with O3 were negative though generally not statistically significant. In the administrative cohorts, virtually all subjects in 2010 had PM2.5 and NO2 annual average exposures below the EU limit values. More than 3.9 million subjects had a residential PM2.5 exposure below the U.S. EPA NAAQS (12 µg/m3) and more than 1.9 million had residential PM2.5 exposures below the WHO guideline (10 µg/m3). We found significant positive associations between PM2.5, NO2, and BC and natural-cause, respiratory, cardiovascular, and lung cancer mortality, with moderate to high heterogeneity between cohorts. We found positive but statistically nonsignificant associations with diabetes mortality. In our main model meta-analysis, the HRs (95% CI) for natural-cause mortality were 1.05 (CI = 1.02, 1.09) for an increase of 5 µg/m3 PM2.5, 1.04 (CI = 1.02, 1.07) for an increase of 10 µg/m3 NO2, and 1.04 (CI = 1.02, 1.06) for an increase of 0.5 × 10-5/m BC, and 0.95 (CI = 0.93, 0.98) for an increase of 10 µg/m3 O3. The shape of the concentration-response functions differed between cohorts, though the associations were generally linear to supralinear, with no indication of a level below which no associations were found. Subset analyses documented that these associations remained at low levels: below 10 µg/m3 for PM2.5 and 20 µg/m3 for NO2. BC and NO2 remained significantly associated with mortality in two-pollutant models with PM2.5 and O3. The PM2.5 HR attenuated to unity in a two-pollutant model with NO2. The negative O3 association was attenuated to unity and became nonsignificant. The mortality associations were robust to alternative specifications of exposure, including time-varying exposure analyses. Time-varying exposure natural spline analyses confirmed associations at low pollution levels. Effect estimates in the youngest participants (<65 years at baseline) were much larger than in the elderly (>65 years at baseline). Effect estimates obtained with the ELAPSE PM2.5 model did not differ from the MAPLE PM2.5 model on average, but in individual cohorts, substantial differences were found. CONCLUSIONS: Long-term exposure to PM2.5, NO2, and BC was positively associated with natural-cause and cause-specific mortality in the pooled cohort and the administrative cohorts. Associations were found well below current limit values and guidelines for PM2.5 and NO2. Associations tended to be supralinear, with steeper slopes at low exposures with no indication of a threshold. Two-pollutant models documented the importance of characterizing the ambient mixture with both NO2 and PM2.5. We mostly found negative associations with O3. In two-pollutant models with NO2, the negative associations with O3 were attenuated to essentially unity in the mortality analysis of the administrative cohorts and the incidence analyses in the pooled cohort. In the mortality analysis of the pooled cohort, significant negative associations with O3 remained in two-pollutant models. Long-term exposure to PM2.5, NO2, and BC was also positively associated with morbidity outcomes in the pooled cohort. For stroke, asthma, and COPD, positive associations were found for PM2.5, NO2, and BC. For acute coronary heart disease, an increased HR was observed for NO2. For lung cancer, an increased HR was found only for PM2.5. Associations mostly showed steeper slopes at low exposures with no indication of a threshold.

[Interrupting the chains of transmission of COVID-19 in Italy: survey among the Prevention Departments]. / Interrompere le catene di trasmissione di COVID-19 in Italia: indagine tra i Dipartimenti di prevenzione.

BACKGROUND: the ability to implement effective preventive and control measures is rooted in public health surveillance to promptly identify and isolate contagious patients. OBJECTIVES: to describe some organizational aspects and resources involved in the control of COVID-19 pandemic. DESIGN: observational cross sectional study. SETTING AND PARTICIPANTS: a survey of methods and tools adopted by the competent service (Prevention department) in the Local public health units (LHU) of the regional Health services has been performed in May 2020. The survey collected data related to activities carried out during the month of April 2020 on the surveillance system for collection of suspected cases, their virological ascertainment, the isolation procedures and contact-tracing activities by means of an online questionnaire filled in by the public health structure of the regional health system. A convenience sample of Prevention departments was recruited. RESULTS: in 44 Prevention departments of 14 Regions/Autonomous Provinces (caring for 40% of the population residing in Italy), different services were swiftly engaged in pandemic response. Reports of suspected cases were about 3 times the number of confirmed cases in the same month. Local reporting form was used in 46% of the LHUs while a regional form was available in 42% of the Departments (in 9/14 Regions). In one fourth the forms were not always used and 2% had no forms for the reporting of suspected cases. Data were recorded in 52% of LHUs on local databases, while in 20% a regional database (in 7 Regions) had been created. A proportion of 11% did not record the data for further elaboration. The virological assessment with nasopharyngeal swabs out of the hospital setting was carried out on the average in 7 points in each LHU (median 5) and the average daily capacity was 350 (71 per 100,000) swabs. The rate of subjects newly tested during the month of April was of 893 per 100,000 new people. Data collected at the swabbing were recorded on a regional platform in 17 LHUs (39%) of 8 Regions. In 7% LHUs only positive specimens were recorded electronically. Local files were used in 27% LHUs. The interview with confirmed cases was carried out with a local questionnaire in 52% LHUs, while 14% stated that a standardized form was not used. The data collected about cases were recorded on a regional IT platform in 30% Departments (in 8 Regions) and in 41% data were registered only locally. For each confirmed case in April, a median of 4 contacts were identified. Only 13 (30%) Departments in 9 Regions have registered contact data on a regional database. Ten Departments (23%) have only hard copies, while 56% recorded data on local databases. About 5 health professionals for 100,000 resident population were involved in each LHU in each of the following activities as receiving reports of suspected cases, swabs collection, interviews of cases and contact identifications. CONCLUSIONS: the pandemic required rapidly a great organizational effort and great flexibility to increase response capacity, which now must be strengthened and maintained. Several different tools (forms and electronic files) have been developed in each LHU and used for the same surveillance operational processes with a loss in local efficiency. The inhomogeneous data collection and recording is an obstacle for further analyses and risk identifications and is a missed opportunity for the advancement of our knowledge on pandemic epidemiology analysis. In Italy, updating the pandemic response plans is the priority, at national, regional and local level, and the occasion to fill the gaps and to improve surveillance systems to the interruption of COVID-19 transmission.

Long-term exposure to air pollution and hospitalization for dementia in the Rome longitudinal study.

BACKGROUND: Few studies have explored the role of air pollution in neurodegenerative processes, especially various types of dementia. Our aim was to evaluate the association between long-term exposure to air pollution and first hospitalization for dementia subtypes in a large administrative cohort. METHODS: We selected 350,844 subjects (free of dementia) aged 65-100 years at inclusion (21/10/2001) and followed them until 31/12/2013. We selected all subjects hospitalized for the first time with primary or secondary diagnoses of various forms of dementia. We estimated the exposure at residence using land use regression models for nitrogen oxides (NOx, NO2) and particulate matter (PM) and a chemical transport model for ozone (O3). We used Cox models to estimate the association between exposure and first hospitalization for dementia and its subtypes: vascular dementia (Vd), Alzheimer's disease (Ad) and senile dementia (Sd). RESULTS: We selected 21,548 first hospitalizations for dementia (7497 for Vd, 7669 for Ad and 7833 for Sd). Overall, we observed a negative association between exposure to NO2 (10 µg/m3) and dementia hospitalizations (HR = 0.97; 95% CI: 0.96-0.99) and a positive association between exposure to O3, NOx and dementia hospitalizations, (O3: HR = 1.06; 95% CI: 1.04-1.09 per 10 µg/m3; NOx: HR = 1.01; 95% CI: 1.00-1.02 per 20 µg/m3).H. Exposure to NOx, NO2, PM2.5, and PM10 was positively associated with Vd and negatively associated with Ad. Hospitalization for Sd was positively associated with exposure to O3 (HR = 1.20; 95% CI: 1.15-1.24 per 10 µg/m3). CONCLUSIONS: Our results showed a positive association between exposure to NOx and O3 and hospitalization for dementia and a negative association between NO2 exposure and hospitalization for dementia. In the analysis by subtype, exposure to each pollutants (except O3) demonstrated a positive association with vascular dementia, while O3 exposure was associated with senile dementia. The results regarding vascular dementia are a clear indication that the brain effects of air pollution are linked with vascular damage.

[Validation of algorithms for the identification of subjects with chronic disease using health information systems]. / Validazione di algoritmi per l'identificazione di persone con patologia cronica attraverso i dati dei sistemi informativi.

OBJECTIVES: to test the validity of algorithms to identify diabetes, chronic obstructive pulmonary disease (COPD), hypertension, and hypothyroidism from routinely collected health data using information from self-reported diagnosis and laboratory or functional test. SETTING AND PARTICIPANTS: clinical or self-reported diagnosis from three surveys conducted in Lazio Region (Central Italy) between year 2010 and 2014 were assumed as gold standard and compared to the results of the algorithms application to administrative data. MAIN OUTCOME MEASURES: prevalence resulted from administrative data and from information available in the surveys were compared. Sensitivity, specificity, positive predictive value, and positive likelihood ratio of algorithms with respect to self-reported diagnosis, laboratory or functional test, assumed as gold standards, were calculated. RESULTS: we analyzed data of 7,318 subjects (1,545 for diabetes, 1,783 for COPD, 2,448 for hypertension, and 1,542 for hypothyroidism). For hypertension and hypothyroidism, we observed a higher prevalence from laboratory or functional test compared to self-reported diagnosis (54.5% vs. 44.9% and 7.5% vs. 1.5%). Sensitivity of administrative data with respect to self-reported diagnosis resulted 90.9%, 38.5%, 88.3%, and 47.8%, respectively, for diabetes, COPD, hypertension, and hypothyroidism. Respectively, specificity was 97.4%, 91.7%, 84.8% and 91.8%; positive predictive value was 70,9%, 38.1%, 82.6% and 8.1%. All values of positive likelihood ratio resulted moderate (about 5), with exception of the diabetes algorithm and the disease-specific payment exemptions register for hypertension (respectively 35.5 and 17.4). CONCLUSION: hypertension and hypothyroidism resulted markedly underdiagnosed from self-reported data. Case identification algorithms are highly specific, allowing their utilization for selection of cohort of subject affected by chronic diseases. The sub-optimal sensitivity observed for COPD and hypothyroidism could limit the utilization of the algorithms for prevalence estimation.

Health effects of Saharan dust in Sicily Region (Southern Italy). / Effetti sanitari delle sabbie sahariane in Sicilia.

"OBJECTIVES: to investigate the increase of PM10 during Saharan dust outbreaks with adverse health effects in Sicily (Southern Italy), the largest Mediterranean Island. DESIGN: pooled analyses of time series with Poisson regression models to estimate the association between PM10 from different sources (desert and non-desert) and different outcomes. SETTING AND PARTICIPANTS: the four largest cities of Sicily (Palermo, Catania, Syracuse, and Messina) and three macroareas (North- East, South, and West) Sicily was divided into. MAIN OUTCOME MEASURES: daily count of cause-specific (ICD-9 codes) mortality and hospital admissions: natural (0-799), cardiovascular (390-459), and respiratory causes (460-519). RESULTS: 962 days affected by Saharan dust (30% of all days: 2,257) were identified. Significant associations between desert PM10 and natural mortality both in the cities and in the macro-areas were found, with increases of risk and 95% confidence intervals equal to 1.1% (95%CI 0.1-2.1) and 1.1% (95%CI 0.8-1.5) per 10 µg/m3 increase in lag 0-1 PM10, respectively. Weaker estimates were found for cardiorespiratory mortality. Desert PM10 displayed an association with respiratory hospitalizations, especially in the three macroareas (0.5%; 95%CI 0.1-1.0). In contrast, cardiovascular hospitalizations were associated only with non-desert PM10 in the four cities (1.3%; 95%CI 0.4- 2.1%). Higher desert PM10-related mortality was found during the warmer months (period: April-September): 2.7% (95%CI 0.8-4.5) in the four cities and 2.5% (95%CI 1.8%-3.2%) in the three macroareas. CONCLUSIONS PM10 originating from desert was positively associated with mortality and hospitalizations in Sicily. Policies should aim to reduce anthropogenic emissions even in areas with large contribution from desert sources."

Does chronic exposure to high levels of nitrogen dioxide exacerbate the short-term effects of airborne particles?

BACKGROUND: Long-term exposure to air pollutants has been hypothesised as a factor in susceptibility to short-term exposure to particulate matter (PM), but results are not coherent. We studied the short-term effects of PM10 on mortality and assessed whether long-term exposure to nitrogen dioxide (NO2) modifies this association. METHODS: We used a case-crossover design to evaluate daily PM10-related mortality among 124 432 35+ year-old participants who died in Rome between 2001 and 2010 and maintained the same address for at least 5 years before death. Modification of PM10-related mortality by long-term NO2 exposure was determined by two-way interaction, while a three-way interaction was used to assess effect modification of high NO2 levels in population groups defined by sociodemographic position and pre-existing diseases. RESULTS: Mortality increased by 0.82% (0.23-1.41%) for each 10 µg/m3 increase in PM10. Mortality rose by 1.22% (0.17-2.38%) in participants exposed to NO2 levels ≥50 µg/m3 and by 0.69% (0.03-1.34%) in those exposed to levels <50 µg/m3 with no effect modification (p-interaction 0.378). A suggestion of effect modification was seen in 85+-year-olds (3.10%; p-interaction 0.043), as well as in those with a pre-existing arrhythmia (3.26%; p-interaction 0.014) and chronic obstructive pulmonary disease (3.52%; p-interaction 0.042). CONCLUSIONS: Long-term exposure to NO2 is not likely to induce susceptibility to short-term PM10 exposure in the overall population. However, an effect modification of NO2 is probable in the elderly and in those suffering from arrhythmias and chronic obstructive pulmonary disease.

[Health effects of air pollution in Rome in December 2015]. / Inquinamento atmosferico ed effetti sulla salute a Roma nel mese di dicembre 2015.

BACKGROUND: in December 2015 Rome has been interested by a peculiar meteorological situation, with atmospheric stability, no rain and little wind. These factors, coupled with the high pollutant emissions typical of the winter pre-Christmas period (increased use of private cars and domestic heating), caused extreme peaks in air pollution concentrations persisting several weeks. OBJECTIVES: describing daily trends in PM10 over two months, November and December 2015, and their impact on the health of the population of Rome. DESIGN: we analysed PM10 time series in Rome for November and December 2015. We estimated the association between daily PM10 concentrations and daily counts of deaths for natural and cardiorespiratory causes, and urgent hospitalizations/emergency-room visits for cardiorespiratory diseases, by use of Poisson regression models adjusted for time trends, influenza epidemics, and meteorology. These risk estimates have been used to quantify attributable deaths/admissions/visits due to exceedances of daily PM10 concentrations above EU-defined limit values in Rome for the period 29 November-30 December 2015. SETTING AND PARTICIPANTS: Rome, November and December 2015; population resident in Rome and deceased or hospitalized/ admitted to emergency rooms in hospitals within the city. MAIN OUTCOME MEASURES: daily mortality for natural (0+ years), respiratory (0+) or cardiac (35+) causes; urgent (non-scheduled) hospitalizations or admissions to emergency room visits for respiratory (0+) or cardiac (35+) diseases. RESULTS: in December 2015, only three days (10th, 11th, and 26th December) had PM10 concentrations below the EU-limit value of 50 µg/m3. Over the 31 days under analysis (from 29 November to 29 December) we estimated 26 natural deaths attributable to PM10 concentrations above 50 µg/m3. Similarly, we estimated 20 and 30 attributable cases of cardiorespiratory hospitalizations and admissions to emergency room visits, respectively. CONCLUSIONS: monitoring and control of anthropogenic emissions are mandatory in order to minimize the adverse health effects of air pollution, especially during air pollution peaks.