Investigating socioeconomic disparities in lung cancer diagnosis, treatment and mortality: an Italian cohort study.

BACKGROUND: Lung cancer is one of the most lethal cancers worldwide and patient clinical outcomes seem influenced by their socioeconomic position (SEP). Since little has been investigated on this topic in the Italian context, our aim was to investigate the role of SEP in the care pathway of lung cancer patients in terms of diagnosis, treatment and mortality. METHODS: This observational retrospective cohort study included patients discharged in the Lazio Region with a lung cancer diagnosis between 2014 and 2017. In the main analysis, educational level was used as SEP measure. Multivariate models, adjusted for demographic and clinical variables, were applied to evaluate the association between SEP and study outcomes, stratified for metastatic (M) and non-metastatic (NM) cancer. We defined a diagnosis as 'delayed' when patients received their initial cancer diagnosis after an emergency department admission. Access to advanced lung cancer treatments (high-cost, novel and innovative treatments) and mortality were investigated within the 24-month period post-diagnosis. Moreover, two additional indicators of SEP were examined in the sensitivity analysis: one focusing on area deprivation and the other on income-based exemption. RESULTS: A total of 13,251 patients were identified (37.3% with metastasis). The majority were males (> 60%) and over half were older than 70 years. The distribution of SEP levels among patients was as follow: 31% low, 29% medium-low, 32% medium-high and 7% high. As SEP increased, the risks of receiving a delayed diagnosis ((high vs low: M: OR = 0.29 (0.23-0.38), NM: OR = 0.20 (0.16-0.25)) and of mortality ((high vs low M: OR = 0.77 (0.68-0.88) and NM: 0.61 (0.54-0.69)) decreased. Access to advanced lung cancer treatments increased in accordance with SEP only in the M cohort (high vs low: M: OR = 1.57 (1.18-2.09)). The primary findings were corroborated by sensitivity analysis. CONCLUSIONS: Our study highlighted the need of public health preventive and educational programs in Italy, a country where the care pathway of lung cancer patients, especially in terms of diagnosis and mortality, appears to be negatively affected by SEP level.

Cause specific mortality in an Italian pool of asbestos workers cohorts.

BACKGROUND: Asbestos is a known human carcinogen and is causally associated with malignant mesothelioma, lung, larynx and ovarian cancers. METHODS: Cancer risk was studied among a pool of formerly asbestos-exposed workers in Italy. Fifty-two Italian asbestos cohorts (asbestos-cement, rolling-stock, shipbuilding, and other) were pooled and their mortality follow-up was updated to 2018. Standardized mortality ratios (SMRs) were computed for major causes of death considering duration of exposure and time since first exposure (TSFE), using reference rates by region, age and calendar period. RESULTS: The study included 63,502 subjects (57,156 men and 6346 women): 40% who were alive, 58% who died (cause known for 92%), and 2% lost to follow-up. Mortality was increased for all causes (SMR: men = 1.04, 95% confidence interval [CI] 1.03-1.05; women = 1.15, 95% CI 1.11-1.18), all malignancies (SMR: men = 1.21, 95% CI 1.18-1.23; women = 1.29, 95% CI 1.22-1.37), pleural and peritoneal malignancies (men: SMR = 10.46, 95% CI 9.86-11.09 and 4.29, 95% CI 3.66-5.00; women: SMR = 27.13, 95% CI 23.29-31.42 and 7.51, 95% CI 5.52-9.98), lung (SMR: men = 1.28, 95% CI 1.24-1.32; women = 1.26, 95% CI 1.02-1.53), and ovarian cancer (SMR = 1.42, 95% CI 1.08-1.84). Pleural cancer mortality increased during the first 40 years of TSFE (latency), reaching a plateau thereafter. CONCLUSIONS: Analyses by time-dependent variables showed that the risk for pleural neoplasms increased with latency and no longer increases at long TSFE, consistent with with asbestos clearance from the lungs. Peritoneal neoplasm risk increased over all observation time.

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.

Community factors and excess mortality in the COVID-19 pandemic in England, Italy and Sweden.

BACKGROUND: Analyses of coronavirus disease 19 suggest specific risk factors make communities more or less vulnerable to pandemic-related deaths within countries. What is unclear is whether the characteristics affecting vulnerability of small communities within countries produce similar patterns of excess mortality across countries with different demographics and public health responses to the pandemic. Our aim is to quantify community-level variations in excess mortality within England, Italy and Sweden and identify how such spatial variability was driven by community-level characteristics. METHODS: We applied a two-stage Bayesian model to quantify inequalities in excess mortality in people aged 40 years and older at the community level in England, Italy and Sweden during the first year of the pandemic (March 2020-February 2021). We used community characteristics measuring deprivation, air pollution, living conditions, population density and movement of people as covariates to quantify their associations with excess mortality. RESULTS: We found just under half of communities in England (48.1%) and Italy (45.8%) had an excess mortality of over 300 per 100 000 males over the age of 40, while for Sweden that covered 23.1% of communities. We showed that deprivation is a strong predictor of excess mortality across the three countries, and communities with high levels of overcrowding were associated with higher excess mortality in England and Sweden. CONCLUSION: These results highlight some international similarities in factors affecting mortality that will help policy makers target public health measures to increase resilience to the mortality impacts of this and future pandemics.

Health impact of air pollution and air temperature in Italy: evidence for policy actions

OBJECTIVES: to estimate the impact (number of deaths and attributable fraction) of air pollution (chronic exposure to PM2.5 and NO2) and high summer temperatures (acute exposure) on mortality in Italy. DESIGN: observational study. Time series analysis (for estimating acute effects of air temperature), and computation of deaths attributable to heat/pollution using standard health impact assessment functions. SETTING AND PARTICIPANTS: for the assessment of the impact due to chronic exposure to air pollutants, the study period considered was 2016-2019. For the assessment of the acute effects of air temperature and related impacts, the municipal daily series of deaths from all causes relating to the period 2003-2015 were used. MAIN OUTCOME MEASURES: mortality for all causes (effects and impacts of acute exposure to air temperature), cause-specific mortality (impact of chronic exposure to pollution). RESULTS: concerning chronic exposure to PM2.5, each year during 2016-2019, 72,083 deaths (11.7%) were estimated to be attributable to annual mean levels of PM2.5 above 5 µg/m3 (WHO-2021 Air Quality Guideline value). Of these, 39,628 were estimated in the regions of the Po Valley and 10,232 in the 6 Italian cities with >500,000 inhabitants. With reference to acute effects of air temperature, over 14,500 deaths (2.3%) were estimated to be attributable to daily temperature increases from the 75th to the 99th percentile of the municipality-specific distribution for the year 2015. Conclusions: high air pollution concentrations and summer temperatures are two environmental risk factors extremely relevant for public health. Although the prevention and mitigation interventions carried out in recent years have contributed to reducing the exposure of the population, there are still alarming numbers of deaths attributable to high levels of particulate matter, nitrogen oxides, and air temperature in the Italian population.

[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.

[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.

[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 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.

[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.

A multi-step machine learning approach to assess the impact of COVID-19 lockdown on NO2 attributable deaths in Milan and Rome, Italy.

BACKGROUND: Air pollution is one of the main concerns for the health of European citizens, and cities are currently striving to accomplish EU air pollution regulation. The 2020 COVID-19 lockdown measures can be seen as an unintended but effective experiment to assess the impact of traffic restriction policies on air pollution. Our objective was to estimate the impact of the lockdown measures on NO2 concentrations and health in the two largest Italian cities. METHODS: NO2 concentration datasets were built using data deriving from a 1-month citizen science monitoring campaign that took place in Milan and Rome just before the Italian lockdown period. Annual mean NO2 concentrations were estimated for a lockdown scenario (Scenario 1) and a scenario without lockdown (Scenario 2), by applying city-specific annual adjustment factors to the 1-month data. The latter were estimated deriving data from Air Quality Network stations and by applying a machine learning approach. NO2 spatial distribution was estimated at a neighbourhood scale by applying Land Use Random Forest models for the two scenarios. Finally, the impact of lockdown on health was estimated by subtracting attributable deaths for Scenario 1 and those for Scenario 2, both estimated by applying literature-based dose-response function on the counterfactual concentrations of 10 µg/m3. RESULTS: The Land Use Random Forest models were able to capture 41-42% of the total NO2 variability. Passing from Scenario 2 (annual NO2 without lockdown) to Scenario 1 (annual NO2 with lockdown), the population-weighted exposure to NO2 for Milan and Rome decreased by 15.1% and 15.3% on an annual basis. Considering the 10 µg/m3 counterfactual, prevented deaths were respectively 213 and 604. CONCLUSIONS: Our results show that the lockdown had a beneficial impact on air quality and human health. However, compliance with the current EU legal limit is not enough to avoid a high number of NO2 attributable deaths. This contribution reaffirms the potentiality of the citizen science approach and calls for more ambitious traffic calming policies and a re-evaluation of the legal annual limit value for NO2 for the protection of human health.

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.

[Incidence of cancer among children and adolescents (0-19 years) in Lazio Region (Central Italy), 2009-2015]. / Incidenza di tumori nella popolazione infantile e adolescenziale (0-19 anni) della Regione Lazio, anni 2009-2015.

OBJECTIVES: to investigate, for the first time, the incidence of cancer (years 2009-2015) and geographical distribution among children and adolescents with cancer diagnosis in Lazio Region (Central Italy). DESIGN: to compute incidence rates of childhood cancers from Lazio Region Childhood Cancer Registry (LRCCR) database, established in 2015, and to compare results with national figures for 2012 provided by the Italian cancer registries network (AIRTUM). SETTING AND PARTICIPANTS: all new cases of malignant tumours (behaviour: /3 of ICD-O-3 classification) and all central nervous system tumours were selected, regardless of behaviour (/0, /1, /3) in children and adolescents (0-19 years) registered in the LRCCR data base. MAIN OUTCOME MEASURES: it was computed: • the raw and the direct standardised rates for the 0-14-year and the 15-19-year age groups for total malignant tumours of the ICCC-3 classification by area (province level and municipality of Rome); • Relative Risks (RR) for area-specific rate compared with that of the Lazio Region and 95% Confidence Intervals (95%CI). RESULTS: a total of 1,782 incident cases were recorded in 2009-2015; of these, 91.4% were confirmed by a pathology report. Standardized Incidence Rate for all malignant tumours is 207.2×1,000,000 (95%CI 195.5-219.5) in children and 335.1×1,000,000 (95%CI 308.9-361.2) in adolescents. Compared to the Lazio Region, a higher incidence of tumours is observed in Rome municipality (RR 1.09; 95%CI 0.98-1.20) and in the Frosinone province (RR 1.07; 95%CI 0.91-1.25) for the whole 0-19-year age group. CONCLUSIONS: compared to the pooled AIRTUM figures for 2003-2008, Lazio Region showed a higher incidence for all cancers, both in children and adolescents, and for specific tumours, such as leukaemia in children and thyroid carcinoma in adolescents. Apart from the diverse observation period, these differences may be due to a higher registry sensitivity of the childhood specialized registry compared to general population registries. The observed incidence excesses for specific geographical areas and tumours deserve further investigations. Overall, in its first seven years of activity, the Lazio childhood cancer registry was able to provide reliable epidemiological figures of cancer incidence in children and adolescents in the Italian context.

[Impact of the COVID-19 epidemic on total and cause-specific mortality in Rome (Italy) in 2020]. / Impatto dell'epidemia di COVID-19 sulla mortalità totale e per causa a Roma nel 2020.

OBJECTIVES: to estimate the impact of the COVID-19 epidemic on total and cause-specific mortality in people residing and dead in the Municipality of Rome (Italy) in 2020, and to describe the causes of death of subjects with SARS-CoV-2 infection confirmed by molecular test. DESIGN: descriptive analysis of total and cause-specific mortality in 2020 in Rome and comparison with a reference period (2015-2018 for total mortality and 2018 for cause-specific mortality); descriptive analysis of cause-specific mortality in the cohort of SARS-CoV-2 infected subjects. SETTING AND PARTICIPANTS: 27,471 deaths registered in the Lazio mortality-cause Registry, relating to people residing and died in the municipality of Rome in 2020, 2,374 of which died from COVID-19.MAIN OUCOME MEASURES: all-cause mortality by month, gender, age group and place of death, cause-specific mortality (ICD-10 codes). RESULTS: in the municipality of Rome in 2020, an excess of mortality from all causes equal to +10% was observed, with a greater increase in the months of October-December (+27%, +56%, and +26%, respectively) in people aged 50+, with the greatest contribution from the oldest age groups (80+) who died in the nursing homes or at home. Lower mortality was observed in the age groups 0-29 years (-30%) and 40-49 years (-13%). In 2020, COVID-19 represents the fourth cause of death in Rome after malignant tumours, diseases of the circulatory system, and respiratory diseases. Excess mortality was observed from stroke and pneumonia (both in men and women), from respiratory diseases (in men), from diabetes, mental disorders, dementia and Parkinson's disease (in women). On the contrary, mortality is lower for all cancers, for diseases of the blood and haematopoietic organs and for the causes of the circulatory system. The follow-up analysis of SARS-CoV-2 positive subjects residing in Rome shows that a share of deaths (about 20%) reports other causes of death such as cardiovascular diseases, malignant tumours, and diseases of the respiratory system on the certificate collected by the Italian National Statistics Institute. CONCLUSIONS: the 2020 mortality study highlighted excesses for acute and chronic pathologies, indicative of possible delays in the diagnosis or treatment of conditions indirectly caused by the pandemic, but also a share of misclassification of the cause of death that is recognized as COVID-19 death.

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

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

Real world data to identify target population for new CAR-T therapies.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoma often refractory to currently available treatments (immuno-chemotherapy/autologous-stem-cell-transplantation-ASCT). Recently, new cell therapies have been approved for patients failing two conventional treatments, CAR-T (Chimeric-Antigen-Receptor-T-cell), committing payers in planning and implementing their use. We aim to define, using Real World Data (RWD), a reproducible procedure that allows identification of CAR-T target population for DLBCL. METHODS: Through the linking of electronic healthcare datasets (EHD), we identified patients with non-Hodgkin's Lymphoma (NHL), resident in Lazio region (2010-2015), aged ≥20 years. DLBCL patients were followed using pathological anatomy (PA) reports, up to 3 years. To be defined as relapsed after two treatment lines, patients must have had new chemotherapy and/or NHL hospitalization after ASCT or at the end of the second chemotherapy. The incident rate of second relapse (R2-rate) was extended to the population without PA reports. RESULT: NHL incident patients were 7384, 68% presented a PA report and, 29% of these had DLBCL codes. Patients who relapsed after two treatment lines were 47 (39%) in the subgroup of patients who received ASCT and 138 (41%) in that with second chemotherapy treatment. Patients in the two subgroups were very different in terms of age and comorbidity. The annual incident number of DLBCL was estimated to be 329 which multiplied by R2-rate (13.7%) gives 45 patients per year eligible for CAR-T. DISCUSSION: This study shows how RWD allows the identification of a target population with new advanced therapies. This approach is rigorous, transparent and verifiable over time.

Green spaces and cognitive development at age 7 years in a rome birth cohort: The mediating role of nitrogen dioxide.

Introduction There is evidence of improvement on mental health and well-being due to contact with green spaces, through various mechanisms and with potentially differential impacts in different populations. Many of these studies have been conducted among adults, while children have not been sufficiently investigated. This study aimed to evaluate the association between residential exposure to greenness and cognitive development at age 7 and to evaluate nitrogen dioxide (NO2) as a potential mediator of this association.Methods This longitudinal study was based on a cohort of newborns enrolled at delivery in two large obstetric hospitals in Rome. We assessed cognitive development at 7 years of age through the Wechsler Intelligence Scale for Children-III edition (WISC-III). We estimated residential surrounding greenness, using satellite derived Normalized Difference Vegetation Index (NDVI), within 300m and 500m buffers around each residential address at birth. We applied weighted multiple linear regression analyses to study the association between NDVI and the WISC-III cognitive scores, using the inverse probability weighting methodology to correct for potential selection bias. We performed a mediation analysis to evaluate the mediating role of NO2 in the association under study.Results We enrolled 719 children at birth and performed our analyses only on 465 children with data on exposure and outcome. The results were not consistent for the average residential surrounding greenness in 300m buffer. For an IQR increase in greenness within 500m buffer around home addresses at birth we found a progress in Arithmetic subtest (ß:0.39; 90% CI: 0.11-0.6), a test concerning with attention, concentration and numerical reasoning, apart from an indication of the positive association with Full scale IQ and Verbal IQ. This association was partly mediated by reduction in NO2, since adding this pollutant in our model explained 35% (90% CI: 7%-62%) of our estimate.Conclusions Our findings showed an association between residential surrounding greenness within 500m and better scores on attention tests at 7 years of age. The observed association between Arithmetic subtest and NDVI was mediated, in part, by a reduction in NO2. This topic has important public health implications in supporting green urban planning policies and promoting children's well-being.

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.

Evaluation of the ERA5 reanalysis-based Universal Thermal Climate Index on mortality data in Europe.

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 - the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) - as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available.

Industrial odour pollution and human health: a systematic review and meta-analysis.

OBJECTIVE: To conduct a systematic review to evaluate the association between residential or occupational short- and long-term exposure to odour pollution from industrial sources and the health status of the exposed population. METHODS: The searches were conducted in Medline, EMBASE and Scopus in April 2021. Exposure to an environmental odour from industrial sources in population resident near the source or in workers was considered. We considered outcomes for which there was a biological plausibility, such as wheezing and asthma, cough, headache, nausea and vomiting (primary outcomes). We also included stress-related symptoms and novel outcomes (e.g. mood states). Risk of bias was evaluated using the OHAT tool. For primary outcomes, when at least 3 studies provided effect estimates by comparing exposed subjects versus not exposed, we pooled the study-specific estimates of odour-related effect using random effects models. Heterogeneity was evaluated with Higgins I2. RESULTS: Thirty studies were eligible for this review, mainly cross-sectional (n = 23). Only one study involved school-age children and two studies involved workers. Only five studies reported odour effects on objective laboratory or clinical outcomes. Animal Feeding Operations and waste were the most common industrial sources. The overall odds ratios in exposed versus not exposed population were 1.15 (95% CI 1.01 to 1.29) for headache (7 studies), 1.09 (95% CI 0.88 to 1.30) for nausea/vomiting (7 studies), and 1.27 (95% CI 1.10 to 1.44) for cough/phlegm (5 studies). Heterogeneity was a moderate concern. Overall, the body of evidence was affected by a definitely high risk of bias in exposure and outcome assessment since most studies used self-reported information. CONCLUSIONS: Findings underline the public health importance of odour pollution for population living nearby industrial odour sources. The limited evidence for most outcomes supports the need for high quality epidemiological studies on the association between odour pollution and its effects on human health.