Cancer-specific mortality odds ratios in the food, accommodation and beverage activities in Italy.

OBJECTIVES: This study investigated cancer-specific mortality risks of workers employed in food, accommodation and beverage (FAB) activities. METHODS: We performed a case-control study based on countrywide mortality and National Social Insurance data. Adjusted cancer specific mortality odds ratios (MOR) were calculated. We modelled occupational exposure as "ever/never been employed" in FAB activities, using other sectors as reference. Analysis was performed by gender, length of employment and year of smoke banning. RESULTS: About 20,000 cancer deaths in FAB were analysed. Working in restaurants was positively associated with cancer of lung (MOR = 1.24), bladder (MOR = 1.24), pharynx, and larynx. Accommodation was associated with cancer of pharynx (MOR = 1.46), while beverage with cancer of liver (MOR = 1.22). Gender, length of employment and smoke banning were found effective in modifying some risks. CONCLUSIONS: Workers in FAB sectors were at risk for several cancers.

[Acute effects of air pollution and extreme temperatures on cause-specific mortality in Italy. Results of the BIGEPI project.] / Effetti acuti dell'inquinamento atmosferico e delle temperature estreme sulla mortalità causa-specifica in Italia. Risultati del progetto BIGEPI.

INTRODUCTION: Air pollution and extreme temperatures have been associated with multiple adverse health effects, especially on the cardiovascular and respiratory systems. The evidence of a relationship between daily exposures and mortality from metabolic, nervous and mental causes needs to be strengthened. The aim of this study is to investigate the association between daily exposure to fine particulate matter (PM2.5) and extreme temperatures (heat and cold) with cause-specific mortality in the entire Italian population. METHODS: The daily counts of deaths from natural, cardiovascular, respiratory, metabolic, diabetes, nervous and mental causes were provided by Istat at the municipal level for the period 2006-2015. Through the application of machine-learning models based on satellite data and spatiotemporal variables, population-weighted exposures to daily mean PM2.5 (2013-2015) and air temperature (2006-2015) were estimated at municipality level. Time-series models adjusted for seasonal and long-term trends were applied, and associations between the above exposures and different causes of death at the national level were estimated. RESULTS: The study found a marked effect of PM2.5 on deaths from nervous causes, with a % increase of risk (IR%) of 6.55% (95% confidence interval: 3.38%-9.81%) per PM2.5 increases of 10 µg/m3. The study also highlighted significant effects of low and high temperatures on all study outcomes. The effects were greater for high temperatures. In particular, the effects of heat, expressed as a % increase in risk per temperature increase from the 75th to the 99th percentile, show the highest associations with mortality from nervous causes (58.3%; 95%CI: 49.7%-67.5%), mental causes (48.4%; 95%CI: 40.4%-56.9%), respiratory causes 45.8%; 95%CI: 39.7%-52.1%) and metabolic causes (36.9%; 95%CI: 30.6%-43.5%). DISCUSSION: The study showed a strong association between daily exposure to PM2.5 and extreme temperatures, especially heat, with mortality outcomes, especially those under-investigated, such as diabetes, metabolic, nervous and mental causes.

Sector of Employment and Mortality: A Cohort Based on Different Administrative Archives.

Administrative data can be precious in connecting information from different sectors. For the first time, we used data from the National Social Insurance Agency (INPS) to investigate the association between the occupational sectors and both non-accidental and accidental mortality. We retrieved information on occupational sectors from 1974 to 2011 for private sector workers included in the 2011 census cohort of Rome. We classified the occupational sectors into 25 categories and analyzed occupational exposure as ever/never have been employed in a sector or as the lifetime prevalent sector. We followed the subjects from the census reference day (9 October 2011) to 31 December 2019. We calculated age-standardized mortality rates for each occupational sector, separately in men and women. We used Cox regression to investigate the association between the occupational sectors and mortality, producing hazard ratios (HRs) and 95% confidence intervals (95%CI). We analyzed 910,559 30+-year-olds (53% males) followed for 7 million person-years. During the follow-up, 59,200 and 2560 died for non-accidental and accidental causes, respectively. Several occupational sectors showed high mortality risks in men in age-adjusted models: food and tobacco production with HR = 1.16 (95%CI: 1.09-8.22), metal processing (HR = 1.66, 95%CI: 1.21-11.8), footwear and wood (HR = 1.19, 95%CI: 1.11-1.28), construction (HR = 1.15, 95%CI: 1.12-1.18), hotels, camping, bars, and restaurants (HR = 1.16, 95%CI: 1.11-1.21) and cleaning (HR = 1.42, 95%CI: 1.33-1.52). In women, the sectors that showed higher mortality than the others were hotels, camping, bars, and restaurants (HR = 1.17, 95%CI: 1.10-1.25) and cleaning services (HR = 1.23, 95%CI: 1.17-1.30). Metal processing and construction sectors showed elevated accidental mortality risks in men. Social Insurance Agency data have the potential to characterize high-risk sectors and identify susceptible groups in the population.

Long-term residential exposure to air pollution and risk of chronic respiratory diseases in Italy: The BIGEPI study.

Long-term exposure to air pollution has adverse respiratory health effects. We investigated the cross-sectional relationship between residential exposure to air pollutants and the risk of suffering from chronic respiratory diseases in some Italian cities. In the BIGEPI project, we harmonised questionnaire data from two population-based studies conducted in 2007-2014. By combining self-reported diagnoses, symptoms and medication use, we identified cases of rhinitis (n = 965), asthma (n = 328), chronic bronchitis/chronic obstructive pulmonary disease (CB/COPD, n = 469), and controls (n = 2380) belonging to 13 cohorts from 8 Italian cities (Pavia, Turin, Verona, Terni, Pisa, Ancona, Palermo, Sassari). We derived mean residential concentrations of fine particulate matter (PM10, PM2.5), nitrogen dioxide (NO2), and summer ozone (O3) for the period 2013-2015 using spatiotemporal models at a 1 km resolution. We fitted logistic regression models with controls as reference category, a random-intercept for cohort, and adjusting for sex, age, education, BMI, smoking, and climate. Mean ± SD exposures were 28.7 ± 6.0 µg/m3 (PM10), 20.1 ± 5.6 µg/m3 (PM2.5), 27.2 ± 9.7 µg/m3 (NO2), and 70.8 ± 4.2 µg/m3 (summer O3). The concentrations of PM10, PM2.5, and NO2 were higher in Northern Italian cities. We found associations between PM exposure and rhinitis (PM10: OR 1.62, 95%CI: 1.19-2.20 and PM2.5: OR 1.80, 95%CI: 1.16-2.81, per 10 µg/m3) and between NO2 exposure and CB/COPD (OR 1.22, 95%CI: 1.07-1.38 per 10 µg/m3), whereas asthma was not related to environmental exposures. Results remained consistent using different adjustment sets, including bi-pollutant models, and after excluding subjects who had changed residential address in the last 5 years. We found novel evidence of association between long-term PM exposure and increased risk of rhinitis, the chronic respiratory disease with the highest prevalence in the general population. Exposure to NO2, a pollutant characterised by strong oxidative properties, seems to affect mainly CB/COPD.

Asbestos Consumption and Malignant Mesothelioma Mortality Trends in the Major User Countries.

Background: The causal association between mesothelioma and asbestos exposure is conclusive, and many studies have proved that the trend in asbestos use is a strong predictor of the pattern in mesothelioma cases with an adequate latency time (generally around 30-40 years or more). Recently, a novel approach for predicting malignant pleural mesothelioma, based on asbestos consumption trend and using distributed non-linear models, has been applied. Objectives: The purpose of this study is to analyse trends in asbestos consumption and malignant mesothelioma mortality in the major asbestos-user countries. Furthermore, we applied distributed non-linear models to estimate and compare epidemiological relationships between asbestos consumption and mesothelioma mortality across these countries. Methods: The study involves major asbestos-user countries in which historical asbestos consumption and mesothelioma mortality data are available. Data on asbestos consumption were derived from worldwide asbestos supply and mesothelioma mortality data from World Health Organization (WHO) mortality archives. A quasi-Poisson generalized linear model was used to model past asbestos exposure and male mesothelioma mortality rates in each country. Exposure-response associations have been modelled using distributed lag non-linear models. Findings and conclusions: According to the criteria defined above, we selected 18 countries with raw asbestos cumulative consumptions higher than two million tons in the period 1933-2012. Overall, a clear linear relationship can be observed between total consumption and total deaths for mesothelioma. Country-specific exposure, lag and age-response relationships were identified and common functions extracted by a meta-analysis procedure. Non-linear models appear suitable and flexible tools for investigating the association between mesothelioma mortality and asbestos consumption. There is a need to improve the global epidemiological surveillance of asbestos-related diseases, particularly mesothelioma mortality, and the absence of reliable data for some major asbestos-user countries is a real concern. A reliable assessment of mesothelioma mortality is a fundamental step towards increasing the awareness of related risks and the need of an international ban on asbestos.

Effects of Temperatures and Heatwaves on Occupational Injuries in the Agricultural Sector in Italy.

The effects of heat on health have been well documented, while less is known about the effects among agricultural workers. Our aim is to estimate the effects and impacts of heat on occupational injuries in the agricultural sector in Italy. Occupational injuries in the agricultural sector from the Italian national workers' compensation authority (INAIL) and daily mean air temperatures from Copernicus ERA5-land for a five-year period (2014-2018) were considered. Distributed lag non-linear models (DLNM) were used to estimate the relative risk and attributable injuries for increases in daily mean air temperatures between the 75th and 99th percentile and during heatwaves. Analyses were stratified by age, professional qualification, and severity of injury. A total of 150,422 agricultural injuries were considered and the overall relative risk of injury for exposure to high temperatures was 1.13 (95% CI: 1.08; 1.18). A higher risk was observed among younger workers (15-34 years) (1.23 95% CI: 1.14; 1.34) and occasional workers (1.25 95% CI: 1.03; 1.52). A total of 2050 heat-attributable injuries were estimated in the study period. Workers engaged in outdoor and labour-intensive activities in the agricultural sector are at greater risk of injury and these results can help target prevention actions for climate change adaptation.

Relationship of long-term air pollution exposure with asthma and rhinitis in Italy: an innovative multipollutant approach.

BACKGROUND: air pollution is a complex mixture; novel multipollutant approaches could help understanding the health effects of multiple concomitant exposures to air pollutants. AIM: to assess the relationship of long-term air pollution exposure with the prevalence of respiratory/allergic symptoms and diseases in an Italian multicenter study using single and multipollutant approaches. METHODS: 14420 adults living in 6 Italian cities (Ancona, Pavia, Pisa, Sassari, Turin, Verona) were investigated in 2005-2011 within 11 different study cohorts. Questionnaire information about risk factors and health outcomes was collected. Machine learning derived mean annual concentrations of PM10, PM2.5, NO2 and mean summer concentrations of O3 (µg/m3) at residential level (1-km resolution) were used for the period 2013-2015. The associations between the four pollutants and respiratory/allergic symptoms/diseases were assessed using two approaches: a) logistic regression models (single-pollutant models), b) principal component logistic regression models (multipollutant models). All the models were adjusted for age, sex, education level, smoking habits, season of interview, climatic index and included a random intercept for cohorts. RESULTS: the three-year average (± standard deviation) pollutants concentrations at residential level were: 20.3 ± 6.8 µg/m3 for PM2.5, 29.2 ± 7.0 µg/m3 for PM10, 28.0 ± 11.2 µg/m3 for NO2, and 70.9 ± 4.3 µg/m3 for summer O3. Through the multipollutant models the following associations emerged: PM10 and PM2.5 were related to 14-25% increased odds of rhinitis, 23-34% of asthma and 30-33% of night awakening; NO2 was related to 6-9% increased odds of rhinitis, 7-8% of asthma and 12% of night awakening; O3 was associated with 37% increased odds of asthma attacks. Overall, the Odds Ratios estimated through the multipollutant models were attenuated when compared to those of the single-pollutant models. CONCLUSIONS: this study enabled to obtain new information about the health effects of air pollution on respiratory/allergic outcomes in adults, applying innovative methods for exposure assessment and multipollutant analyses.

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.

Association between extreme temperature exposure and occupational injuries among construction workers in Italy: An analysis of risk factors.

BACKGROUND/AIM: Extreme temperatures have impact on the health and occupational injuries. The construction sector is particularly exposed. This study aims to investigate the association between extreme temperatures and occupation injuries in this sector, getting an insight in the main accidents-related parameters. METHODS: Occupational injuries in the construction sector, with characteristic of accidents, were retrieved from Italian compensation data during years 2014-2019. Air temperatures were derived from ERA5-land Copernicus dataset. A region based time-series analysis, in which an over-dispersed Poisson generalized linear regression model, accounting for potential non-linearity of the exposure- response curve and delayed effect, was applied, and followed by a meta-analysis of region-specific estimates to obtain a national estimate. The relative risk (RR) and attributable cases of work-related injuries for an increase in mean temperature above the 75th percentile (hot) and for a decrease below the 25th percentile (cold) were estimated, with effect modifications by different accidents-related parameters. RESULTS: The study identified 184,936 construction occupational injuries. There was an overall significant effect for high temperatures (relative risk (RR) 1.216 (95% CI: (1.095-1.350))) and a protective one for low temperatures (RR 0.901 (95% CI: 0.843-0.963)). For high temperatures we estimated 3,142 (95% CI: 1,772-4,482) attributable cases during the studied period. RRs from 1.11 to 1.30 were found during heat waves days. Unqualified workers, as well as masons and plumbers, were found to be at risk at high temperatures. Construction, quarry and industrial sites were the risky working environments, as well as specific physical activities like working with hand-held tools, operating with machine and handling of objects. Contact with sharp, pointed, rough, coarse 'Material Agent' were the more risky mode of injury in hot conditions. CONCLUSIONS: Prevention policies are needed to reduce the exposure to high temperatures of construction workers. Such policies will become a critical issue considering climate change.

[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.

[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.

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

OBJECTIVES: to assess the potential of using longitudinal metropolitan studies (LMS) to study the association between long-term exposure to air pollution and the incidence of acute coronary events and stroke. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30 years, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). Annual concentrations of particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2) and warm-season ozone (O3) (annual O3 in Taranto and Brindisi), estimated through satellite (Turin, Bologna, Rome) or photochemical models (Taranto and Brindisi) with a spatial resolution of 1 km2, were assigned to the census address. MAIN OUTCOME MEASURES: incidence of coronary heart disease (CHD) and stroke until 31.12.2018 (2019 in Bologna). Cohort-specific Hazard Ratios (HRs), estimated using Cox regression models progressively adjusting for individual and contextual covariates, were pooled with random-effect meta-analysis. RESULTS: there were 71,872 incident CHD cases and 43,884 incident cases of stroke in almost 18 million person-years. No association was observed between the exposures studied and incidence of CHD and stroke, except for an increase in the incidence of CHD associated with warm-season O3 exposure (HR 1.034 per 5 µg/m3 increase). Some positive associations were found in specific cities (both outcomes in Brindisi with PM10 exposure and in Taranto with NO2 exposure, stroke in Rome with both PM10 and PM2.5), although estimates were not significant in some instances. CONCLUSIONS: LMS are a high potential tool for the study of comparative medium- and long-term effects of air pollution. Their further development (different definitions of exposure, outcomes, characteristics of the urban areas and extension to other LMS) may make them even more valuable tools for monitoring and planning public health interventions.

[Impact of heat and cold on cause -specific mortality in Italy]. / Impatto del caldo e del freddo sulla mortalità per causa in Italia.

OBJECTIVES: to estimate the impact of daily exposure to extreme air temperatures (heat and cold) on cause-specific mortality in Italy and to evaluate the differences in the association between urban, suburban and rural municipalities. DESIGN: time series analyses with two-stage approach were applied: in the first stage, multiple Poisson regression models and distributed lag non-linear models (DLNM) were used to define the association between temperature and mortality; in the second one, meta-analytic results were obtained by adopting BLUP (Best Linear Unbiased Prediction) coefficients at provincial level, which were then used to estimate the Attributable Fractions of cause-specific deaths. SETTING AND PARTICIPANTS: cause-specific deaths from 2006to 2015 in Italy have been analysed by region and overall. MAIN OUTCOME MEASURES: 5,648,299 total deaths included. Fractions (and relative 95% empirical confidence interval) of deaths attributable to increases from 75th to 99th percentiles of temperature, for heat, and decreases from 25th to 1st percentile, for cold. RESULTS: the overall impact of air temperature on causespecificmortality is higher for heat than for cold. When considering heat, the attributable fraction is higher for diseases of the central nervous system (3.6% 95% CI 1.9-4.9) and mental health disease (3.1% 95% CI 1.7-4.4), while considering cold, ischemic disease (1.3% 95% CI 1.1-1.6) and diabetes (1.3% 95% CI 0.7-1.8) showed the greater impact. By urbanization level, similar impacts were found for cold temperature, while for heat there was an indication of higher vulnerability in rural areas emerged. CONCLUSIONS: results are relevant for the implementation and promotion of preventive measures according to climate change related increase in temperature. The available evidence can provide the basis to identify vulnerable areas and population subgroups to which address current and future heat and cold adaptation plans in Italy.

[Long-term exposure to air pollution and natural mortality: variations related to the use of different exposure indicators in the cohorts of BIGEPI project]. / Esposizione di lungo periodo all'inquinamento atmosferico e mortalità naturale: variazioni legate all'utilizzo di diversi indicatori di esposizione nelle coorti del progetto BIGEPI.

OBJECTIVES: appropriate assessment of exposure to air pollution is crucial for the estimation of adverse effects on human health, both in the short and long term. Within the BIGEPI project, different indicators of long-term exposure to air pollution, in association with mortality by cause, were tested within the Italian longitudinal metropolitan studies (LMS). This allowed an evaluation of differences in effect estimates using the different exposure indicators. DESIGN: closed cohort. SETTING AND PARTICIPANTS: subjects aged >=30, who took part in the 2011 census, residents in 5 cities (Turin, Bologna, Rome, Brindisi and Taranto). MAIN OUTCOME MEASURES: at the time of enrolment, residential exposure levels to particulate matter <=10 µm (PM10), PM <=2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3) for the period April-September (O3 warm season) were obtained from models at different spatial resolutions, from 1x1km to 200x200m (from the BEEP project) to 100x100m (ELAPSE project). In addition, locally developed models were used in each area (FARM photochemical model at 1x1-km for the cities of Rome, Taranto and Brindisi, Land-Use Regression (LUR) model for the city of Turin, PESCO model for Bologna). Cox proportional hazards models were applied to assess the association between exposure to air pollution (assessed using different exposure indicators) and natural mortality, adjusting for both individual and area covariates. RESULTS: the exposure levels derived by the different models varied between pollutants, with differences between the averages ranging from 3 to 20% for PM10, from 1 to 23% for PM2.5, and from 3 to 28% for NO2; the results for O3 were more heterogeneous. A total of 267,350 deaths from natural causes were observed. There is low heterogeneity in the effect estimates calculated from different environmental models, while there is greater variability in average exposure values, with different behaviour depending on the model and the characteristics of the area investigated. Differences are more pronounced where local risk factors are relevant, e.g., in industrial cities, thus suggesting the need of considering industrial exposure separately from other sources. CONCLUSIONS: the numerous heterogeneities in the data used make it difficult to draw conclusions about the comparisons studied. Nevertheless, this study suggests that different approaches to the assessment of environmental exposure should be evaluated depending on the national or local level of interest, also according to the specifities of the investigated areas.

[Employment sector and respiratory mortality in Rome and Turin longitudinal metropolitan studies]. / Settore occupazionale e mortalità respiratoria negli studi longitudinali metropolitani di Roma e Torino.

OBJECTIVES: to assess the association between the occupational sector and respiratory mortality in the metropolitan longitudinal studies of Rome and Turin. DESIGN: retrospective cohort study. SETTING AND PARTICIPANTS: the 2011 census cohorts of residents of Rome and Turin aged 30 years and older who had worked for at least one year in the private sector between 1970s and 2011 was analysed. The individuals included in the study were followed from 9 October 2011 to 31 December 2018. Occupational history was obtained from archives of private sector contributions at the National Social Insurance Agency (INPS) and then was linked to data from the longitudinal studies. MAIN OUTCOME MEASURES: the study outcome was non-malignant respiratory mortality. The exposure of interest was whether or not individuals had worked in one of the 25 occupational sectors considered (agriculture and fishing, steel industry, paper and printing, pharmaceuticals, manufacturing, textile, energy and water, food and tobacco industry, non-metal mining, glass & cement industry, metal processing, electrical construction, footwear and wood industry, construction, trade, hotel and restaurants, transportation, insurance, healthcare, services, laundries, waste management, hairdressing, cleaning services, and gas stations). The association between the occupational sector and respiratory mortality, adjusted for potential confounders (age, marital status, place of birth, educational level), was estimated using Cox models. All analyses were stratified by sex and city. RESULTS: a total of 910,559 people were analysed in Rome and 391,541 in Turin. During the eight years of follow-up, 4,133 people in Rome and 2,772 people in Turin died from respiratory causes. The sectors associated with high respiratory mortality in both cities among men were footwear and wood industry (adjusted HR for age: 1.37 (95%CI 1.07-1.76) and 1.48 (95%CI 1.08-2.03) in Rome and Turin, respectively), construction (HR: 1.31 (95%CI 1.20-1.44) in Rome and 1.51 (95%CI 1.31-1.74) in Turin), hotel and restaurant sector (HR: 1.25 (95%CI 1.07-1.46) in Rome and 1.68 (95%CI 1.20-2.33) in Turin), and cleaning services (HR: 1.57 (95%CI 1.19-2.06) in Rome and 1.97 (95%CI 1.51-2.58) in Turin). Some sectors had high respiratory mortality only in one of the two cities: in Rome, the food& tobacco industry, and gas stations, while in Turin, the metal processing industry. Among female workers, the cleaning services sector was associated with higher respiratory mortality in both Rome and Turin (HR: 1.52, 95%CI 1.27-1.82, e 1.58, 95%CI 1.17-2.12, respectively). CONCLUSIONS: the data confirm the previously known associations between occupational sectors and respiratory mortality for exposures characteristic of specific sectors, such as construction, hotel and restaurant sector, and cleaning services. The differences reported between the two cities reflect the different composition of the workforce and the size of the two study populations. Administrative social insurance data can provide helpful information for epidemiological studies of occupational exposure.

[The role of exposure to airborne pollutants in the workplace on the prevalence and severity of chronic respiratory disease in Italy]. / Il ruolo dell'esposizione a inquinanti aerodispersi nel luogo di lavoro sulla prevalenza e gravità della malattia respiratoria cronica in Italia.

OBJECTIVES: occupational exposure to vapours, gases, dusts and fumes (VGDF) plays an important role in the development and exacerbation of respiratory diseases. The aim of this study is to evaluate the possible association of occupational exposure to airborne pollutants and chronic respiratory diseases. DESIGN: multicase-control study. SETTING AND PARTICIPANTS: cases of chronic respiratory diseases and controls from the Italian multicentric study Gene Environment Interaction in Respiratory Diseases (GEIRD). MAIN OUTCOME MEASURES: the occurrence of rhinitis, asthma, chronic bronchitis/chronic obstructive pulmonary disease (COPD), asthma severity, spirometry data, exhaled nitric oxide (FeNO) were examined in relation to chronic and acute occupational exposures to airborne pollutants using multiple regression models. RESULTS: 2,943 subjects were enrolled in the study. Regularm exposure to VGDF was associated with a higher prevalence of chronic bronchitis/COPD (OR 1.40, 95%CI 0.98-1.99), especially in those also having asthma (OR 1.80, 95%CI 1.14-2.85), a lower prevalence of remittent asthma (OR 0.53, 95%CI 0.29-0.96) and, in those with asthma, an increased activity of the disease (severity score) (OR 1.77, 95%CI 1.20-2.60). No associations were observed between occupational exposure and prevalence of rhinitis, spirometry and FeNO data. Finally, an association was found between acute exposure to airborne pollutants (occupational and non-occupational) and the respiratory diseases investigated, in particular active asthma and asthma associated chronic bronchitis/BPCO. CONCLUSIONS: these data confirm a significant role of occupational exposure to airborne pollutants on respiratory health, underlying the importance of workplace exposure prevention, in particular for more susceptible subjects, as those with respiratory diseases.

An occupational health risk index: definition, description and mapping at municipality level.

OBJECTIVES: to develop an occupational health risk index that can help to introduce the occupational risk component into epidemiological studies and assess the level of occupational risk in Italian municipalities useful for supporting prevention measures. DESIGN: defi nition of a municipal index as a combination of occupational and territorial indicators derived from national registers of occupational data and environmental archives. SETTING AND PARTICIPANTS: the index composition is based on data on work injuries, occupational diseases and workers exposed to carcinogens in the years 2015-2019 available at the municipal level, as well as data on municipalities hosting sites of national interest for environmental remediation (SIN) and those in which big industrial facilities (GIE), registered as pollutant emitters, are located. MAIN OUTCOME MEASURES: standardized rates of occupational injuries and occupational diseases occurred in Italian municipalities were calculated from data collected by the Italian National Institute for Insurance against Accidents at Work (Inail) in relation to the working-age population (15-69 and 15+ for injuries and occupational diseases, respectively), estimated by the Italian National Statistical Institute (Istat) in 2018. In addition, data from the National Information System on Occupational Exposure to carcinogens (SIREP) were included, from which raw rates were calculated at municipal level. Finally, two other indicators were included, describing the presence/absence of a SIN and the number of GIEs industrial facilities in each municipality. The index of occupational health risk (INDORS) is calculated by summing standardised values of the above fi ve indicators as a continuous variable and it was also classifi ed by quintiles of population as a categorical variable. The association between cause-specific mortality and INDORS levels was evaluated using data on mortality occurring in 2015. RESULTS: during the observation period 2,011,457, 131,353 and 140,183 events were recorded for injuries, occupational diseases and workers exposed to carcinogens, mainly among male workers. A municipal map of INDORS levels (1-5) shows a strong South-North gradient, in line with the Italian industrial geographical context. The contributions of the SIN and GIE indicators are higher in the hot spot municipalities located in the Southern regions and islands. Among the municipalities analysed 1,099 were classifi ed in the lowest risk level, 1,331 in the low-medium level, 1,619 in the medium level, 2,621 in the medium-high level and 1,284 in the highest risk level. The index shows a direct correlation with accidental mortality and an inverse correlation with all-cause and malignant neoplasm mortality. CONCLUSIONS: the proposed index can be useful to introduce the occupational risk dimension in ecological studies and results as a flexible tool to rank Italian municipalities in terms of occupational risk.

Occupational Mortality Matrix: A Tool for Epidemiological Assessment of Work-Related Risk Based on Current Data Sources.

Mortality from occupational diseases significantly afflicts society, in terms of both economic costs and human suffering. The International Labour Organization (ILO) estimated that 2.4 million workers die from work-related diseases every year. In Europe, around 80,000 workers die from cancer attributed to occupational exposure to carcinogens. This study developed the Occupational Mortality Matrix (OMM) aimed to identify significant associations between causes of death and occupational sectors through an individual record linkage between mortality data and the administrative archive of occupational histories. The study population consisted of 6,433,492 deceased subjects in Italy (in the period 2005-2015), of which 2,723,152 records of work histories were retrieved (42%). The proportional mortality ratio (PMR) was estimated to investigate the excess of mortality for specific causes associated with occupational sectors. Higher PMRs were reported for traditionally risky occupations such as shipbuilding for mesothelioma cases (PMR: 8.15; 95% CI: 7.28-9.13) and leather production for sino-nasal cancer (PMR: 5.04; 95% CI: 3.54-7.19), as well as for unexpected risks such as male breast cancer in the pharmaceutical industry (PMR: 2.56; 95% CI: 1.33-4.93) and brain cancer in railways (PMR: 1.43; 95% CI: 1.24-1.66). The OMM proved to be a valid tool for research studies to generate hypotheses about the occupational etiology of diseases, and to monitor and support priority actions for risk reduction in workplaces.