Equity in the recovery of elective and oncological surgery volumes after the COVID-19 lockdown: a multicentre cohort study in Italy.

BACKGROUND: The COVID-19 pandemic has had, and still has, a profound impact on national health systems, altering trajectories of care and exacerbating existing inequalities in health. Postponement of surgeries and cancellation of elective surgical procedures have been reported worldwide. In Italy, the lock-down measures following the COVID-19 pandemic caused cancellations of surgical procedures and important backlogs; little is known about potential social inequalities in the recovery process that occurred during the post-lockdown period. This study aims at evaluating whether all population social strata benefited equally from the surgical volumes' recovery in four large Italian regions. METHODS: This multicentre cohort study covers a population of approximately 11 million people. To assess if social inequalities exist in the recovery of eight indicators of elective and oncological surgery, we estimated Risk Ratios (RR) through Poisson models, comparing the incidence proportions of events recorded during COVID-19 (2020-21) with those in pre-pandemic years (2018-19) for each pandemic period and educational level. RESULTS: Compared to 2018-19, volumes of elective surgery showed a U-shape with the most significant drops during the second wave or the vaccination phase. The recovery was socially unequal. At the end of 2021, incidence proportions among highly educated people generally exceeded the expected ones; RRs were 1.31 (95%CI 1.21-1.42), 1.24 (95%CI 1.17-1.23), 1.17 (95%CI 1.08-1.26) for knee and hip replacement and prostatic surgery, respectively. Among low educated patients, RR remained always < 1. Oncological surgery indicators showed a similar social gradient. Whereas volumes were preserved among the highly educated, the low educated were still lagging behind at the end of 2021. CONCLUSIONS: Surgical procedures generally returned to pre-pandemic levels but the low educated experienced the slowest recovery. An equity-oriented appraisal of trends in healthcare provision should be included in pandemic preparedness plans, to ensure that social inequalities are promptly recognised and tackled.

Long-term exposure to air pollution and chronic kidney disease-associated mortality-Results from the pooled cohort of the European multicentre ELAPSE-study.

Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5 µm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289,564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5 µg/m3, BC (1.26 (1.03-1.53) per 0.5 × 10- 5/m), NO2 (1.13 (0.93-1.38) per 10 µg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10 µg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.

SARS-CoV-2 spread and area economic disadvantage in the italian three-tier restrictions: a multilevel approach.

BACKGROUND: To face the second wave of COVID-19, Italy implemented a tiered restriction system with different limitation levels (yellow = medium; orange = medium-high, red = high) at the beginning of November 2020. The restrictions systematically reduced the transmission of SARS-CoV-2 with increasing strength for increasing tier. However, it is unknown whether the effect of limitations was equal between provinces with different socioeconomic levels. Therefore, we investigated the association between the province's socioeconomic level and SARS-CoV-2 infection daily reproduction number in each restriction level. METHODS: We measured the province's socioeconomic level as the percentage of individuals whose 2019 total yearly income was lower than 10,000€, using the measure as a proxy of economic disadvantage. We estimated the daily reproduction number (Rt) at the province level using the SARS-CoV-2 daily incidence data from November 2020 to May 2021. We then used multilevel linear regression models with random intercepts stratified by restriction level to estimate the association between economic disadvantage and Rt. We also adjusted the analyses for potential confounders of the association between the province's economic disadvantage and the Rt: the percentage of people with 0-5 years, the quartiles of population density, and the geographical repartition. RESULTS: Overall, we found increasing Rt in yellow (+ 0.004 p < 0.01, from Rt = 0.99 to 1.08 in three weeks) and containing effects for the orange (-0.005 p < 0.01, from Rt = 1.03 to 0.93) and the red tier (-0.014 p < 0.01, from Rt = 1.05 to 0.76). More economically disadvantaged provinces had higher Rt levels in every tier, although non-significantly in the yellow level (yellow = 0.001 p = 0.19; orange = 0.002 p = 0.02; red = 0.004 p < 0.01). The results showed that the association between economic disadvantage and Rt differed by level of restriction. The number of days into the restriction and the economic disadvantage had statistically significant interactions in every adjusted model. Compared to better off, more economically disadvantaged provinces had slower increasing trends in yellow and steeper Rt reductions in orange, but they showed slower Rt reductions in the highest tier. CONCLUSION: Lower tiers were more effective in more economically disadvantaged provinces, while the highest restriction level had milder effects. These results underline the importance of accounting for socioeconomic level when implementing public health measures.

[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.

[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 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.

Long-term exposure to low-level air pollution and incidence of asthma: the ELAPSE project.

BACKGROUND: Long-term exposure to ambient air pollution has been linked to childhood-onset asthma, although evidence is still insufficient. Within the multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we examined the associations of long-term exposures to particulate matter with a diameter <2.5 µm (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) with asthma incidence in adults. METHODS: We pooled data from three cohorts in Denmark and Sweden with information on asthma hospital diagnoses. The average concentrations of air pollutants in 2010 were modelled by hybrid land-use regression models at participants' baseline residential addresses. Associations of air pollution exposures with asthma incidence were explored with Cox proportional hazard models, adjusting for potential confounders. RESULTS: Of 98 326 participants, 1965 developed asthma during a mean follow-up of 16.6 years. We observed associations in fully adjusted models with hazard ratios of 1.22 (95% CI 1.04-1.43) per 5 µg·m-3 for PM2.5, 1.17 (95% CI 1.10-1.25) per 10 µg·m-3 for NO2 and 1.15 (95% CI 1.08-1.23) per 0.5×10-5 m-1 for BC. Hazard ratios were larger in cohort subsets with exposure levels below the European Union and US limit values and possibly World Health Organization guidelines for PM2.5 and NO2. NO2 and BC estimates remained unchanged in two-pollutant models with PM2.5, whereas PM2.5 estimates were attenuated to unity. The concentration-response curves showed no evidence of a threshold. CONCLUSIONS: Long-term exposure to air pollution, especially from fossil fuel combustion sources such as motorised traffic, was associated with adult-onset asthma, even at levels below the current limit values.

IGFBP7 and GDF-15, but not P1NP, are associated with cardiac alterations and 10-year outcome in an elderly community-based study.

BACKGROUND: Little is known about the clinical value of Insulin-like growth factor-binding protein-7 (IGFBP7), a cellular senescence marker, in an elderly general population with multiple co-morbidities and high prevalence of asymptomatic cardiovascular ventricular dysfunction. Inflammation and fibrosis are hallmarks of cardiac aging and remodelling. Therefore, we assessed the clinical performance of IGFBP7 and two other biomarkers reflecting these pathogenic pathways, the growth differentiation factor-15 (GFD-15) and amino-terminal propeptide of type I procollagen (P1NP), for their association with cardiac phenotypes and outcomes in the PREDICTOR study. METHODS: 2001 community-dwelling subjects aged 65-84 years who had undergone centrally-read echocardiography, were selected through administrative registries. Atrial fibrillation (AF) and 4 echocardiographic patterns were assessed: E/e' (> 8), enlarged left atrial area, left ventricular hypertrophy (LVH) and reduced midwall circumference shortening (MFS). All-cause and cardiovascular mortality and hospitalization were recorded over a median follow-up of 10.6 years. RESULTS: IGFBP7 and GDF-15, but not P1NP, were independently associated with prevalent AF and echocardiographic variables after adjusting for age and sex. After adjustment for clinical risk factors and cardiac patterns or NT-proBNP and hsTnT, both IGFBP7 and GDF-15 independently predicted all-cause mortality, hazard ratios 2.13[1.08-4.22] and 2.03[1.62-2.56] per unit increase of Ln-transformed markers, respectively. CONCLUSIONS: In a community-based elderly cohort, IGFBP7 and GDF-15 appear associated to cardiac alterations as well as to 10-year risk of all-cause mortality.

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.

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.

Sex differences in factors associated with heart failure and diastolic left ventricular dysfunction: a cross-sectional population-based study.

BACKGROUND: Although sex differences in cardiovascular diseases are recognised, including differences in incidence, clinical presentation, response to treatments, and outcomes, most of the practice guidelines are not sex-specific. Heart failure (HF) is a major public health challenge, with high health care expenditures, high prevalence, and poor clinical outcomes. The objective was to analyse the sex-specific association of socio-demographics, life-style factors and health characteristics with the prevalence of HF and diastolic left ventricular dysfunction (DLVD) in a cross-sectional population-based study. METHODS: A random sample of 2001 65-84 year-olds underwent physical examination, laboratory measurements, including N-terminal pro-B-type natriuretic peptide (NT-proBNP), electrocardiography, and echocardiography. We selected the subjects with no missing values in covariates and echocardiographic parameters and performed a complete case analysis. Sex-specific multivariable logistic regression models were used to identify the factors associated with the prevalence of the diseases, multinomial logistic regression was used to investigate the factors associated to asymptomatic and symptomatic LVD, and spline curves to display the relationship between the conditions and both age and NT-proBNP. RESULTS: In 857 men included, there were 66 cases of HF and 408 cases of DLVD (77% not reporting symptoms). In 819 women, there were 51 cases of HF and 382 of DLVD (79% not reporting symptoms). In men, the factors associated with prevalence of HF were age, ischemic heart disease (IHD), and suffering from three or more comorbid conditions. In women, the factors associated with HF were age, lifestyles (smoking and alcohol), BMI, hypertension, and atrial fibrillation. Age and diabetes were associated to asymptomatic DLVD in both genders. NT-proBNP levels were more strongly associated with HF in men than in women. CONCLUSIONS: There were sex differences in the factors associated with HF. The results suggest that prevention policies should consider the sex-specific impact on cardiac function of modifiable cardiovascular risk factors.

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.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

[Mortality inequalities in Rome: the role of individual education and neighbourhood real estate market]. / Differenziali di mortalità a Roma: il ruolo dell'istruzione e dei prezzi immobiliari del quartiere di residenza.

OBJECTIVES: to investigate the association between real estate prices, education, and mortality. DESIGN: cohort study. SETTING AND PARTICIPANTS: residents in Rome at the 2011 Italian Census, not living in institutions, and living in the address reported in the Census survey. People aged 18-99 years were followed from 2011 to 2016 using anonymous record linkage procedures with administrative databases. The Census includes several individual information, such as gender, age, education, residential neighbourhood. Data and cause of death were collected from mortality register. Real estate prices (euros/m2) were available for each neighbourhood. MAIN OUTCOME MEASURES: adjusted Cox regression models (hazard ratios - HRs and 95%CIs) were used to estimate the association among individual education, real estate price in the neighbourhood, and mortality. RESULTS: the subjects selected were 2,051,376 (54% women, 22.5% with high education level). During the follow-up, 127,352 subjects died. Taking into account gender, age, marital status, and real estate prices, education level was strongly associated with all-cause mortality; compared to highly educated the higher mortality, risk was 35% (95%CI 32%-37%) for low education level and 16% (95%CI 14%-19%) for medium education level. Taking into account the same factors and education level, each increase of 1,000 euros in price/m2 was inversely associated with mortality (HR 0.96, 95%CI 0.96-0.97). CONCLUSIONS: there is an independent association between the two indicators and mortality in Rome. A simple indicator such as real estate prices can be used to tackle inequalities.

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.

Predictive value of interatrial block for atrial fibrillation in elderly subjects enrolled in the PREDICTOR study.

AIMS: The principal aims of this prospective multicentre study were to relate the presence of interatrial block (IAB) with a late occurrence of atrial fibrillation (AF) and to demonstrate the independence of the IAB effect on risk of AF from structural cardiac alterations. METHODS: This prospective study was the follow-up of subjects included in the PREDICTOR cross-sectional population-based study. Subjects were divided into groups according to IAB status. Socio-demographic and health characteristic were collected during enrolment in the PREDICTOR along with ECGs, echocardiograms and NT-proBNP dosages. Follow up was performed on administrative data. The mean time of follow up was 6.6 years. RESULTS: 1626 subjects were included in the analysis. Four hundred-fifteen subjects out of 1626 (25.5%) had IAB. The survival analysis suggests an association between IAB alone and AF (HR = 1.50, p = 0.058) and, in normal-weight subjects, IAB strongly predicted AF indicating more than triple the risk (HR = 3.05; p = 0.002 95% CI: 1.51-6.18). The association seems to be independent of possible confounders such as history of IHD, left ventricular hypertrophy, CHA2DS2-VASc, left atrial dimension, or NT-proBNP dosage. CONCLUSION: Our analysis suggests that IAB is an electric condition that can increase the risk of AF independently of any structural cardiac alterations, at least in normal-weight subjects.

Air pollution and incidence of cancers of the stomach and the upper aerodigestive tract in the European Study of Cohorts for Air Pollution Effects (ESCAPE).

Air pollution has been classified as carcinogenic to humans. However, to date little is known about the relevance for cancers of the stomach and upper aerodigestive tract (UADT). We investigated the association of long-term exposure to ambient air pollution with incidence of gastric and UADT cancer in 11 European cohorts. Air pollution exposure was assigned by land-use regression models for particulate matter (PM) below 10 µm (PM10 ), below 2.5 µm (PM2.5 ), between 2.5 and 10 µm (PMcoarse ), PM2.5 absorbance and nitrogen oxides (NO2 and NOX ) as well as approximated by traffic indicators. Cox regression models with adjustment for potential confounders were used for cohort-specific analyses. Combined estimates were determined with random effects meta-analyses. During average follow-up of 14.1 years of 305,551 individuals, 744 incident cases of gastric cancer and 933 of UADT cancer occurred. The hazard ratio for an increase of 5 µg/m3 of PM2.5 was 1.38 (95% CI 0.99; 1.92) for gastric and 1.05 (95% CI 0.62; 1.77) for UADT cancers. No associations were found for any of the other exposures considered. Adjustment for additional confounders and restriction to study participants with stable addresses did not influence markedly the effect estimate for PM2.5 and gastric cancer. Higher estimated risks of gastric cancer associated with PM2.5 was found in men (HR 1.98 [1.30; 3.01]) as compared to women (HR 0.85 [0.5; 1.45]). This large multicentre cohort study shows an association between long-term exposure to PM2.5 and gastric cancer, but not UADT cancers, suggesting that air pollution may contribute to gastric cancer risk.

Air Pollution Exposure During Pregnancy and Symptoms of Attention Deficit and Hyperactivity Disorder in Children in Europe.

BACKGROUND: Exposure to air pollution during pregnancy may increase attention-deficit/hyperactivity disorder (ADHD) symptoms in children, but findings have been inconsistent. We aimed to study this association in a collaborative study of eight European population-based birth/child cohorts, including 29,127 mother-child pairs. METHODS: Air pollution concentrations (nitrogen dioxide [NO2] and particulate matter [PM]) were estimated at the birth address by land-use regression models based on monitoring campaigns performed between 2008 and 2011. We extrapolated concentrations back in time to exact pregnancy periods. Teachers or parents assessed ADHD symptoms at 3-10 years of age. We classified children as having ADHD symptoms within the borderline/clinical range and within the clinical range using validated cutoffs. We combined all adjusted area-specific effect estimates using random-effects meta-analysis and multiple imputations and applied inverse probability-weighting methods to correct for loss to follow-up. RESULTS: We classified a total of 2,801 children as having ADHD symptoms within the borderline/clinical range, and 1,590 within the clinical range. Exposure to air pollution during pregnancy was not associated with a higher odds of ADHD symptoms within the borderline/clinical range (e.g., adjusted odds ratio [OR] for ADHD symptoms of 0.95, 95% confidence interval [CI] = 0.89, 1.01 per 10 µg/m increase in NO2 and 0.98, 95% CI = 0.80, 1.19 per 5 µg/m increase in PM2.5). We observed similar associations for ADHD within the clinical range. CONCLUSIONS: There was no evidence for an increase in risk of ADHD symptoms with increasing prenatal air pollution levels in children aged 3-10 years. See video abstract at, http://links.lww.com/EDE/B379.

Traffic-related air pollution and childhood obesity in an Italian birth cohort.

BACKGROUND: Air pollution is associated with several adverse health outcomes in children, such as respiratory illnesses and cognitive development impairment. There are suggestions of an effect of traffic-related air pollution on the occurrence of childhood obesity, but the results are not consistent. OBJECTIVES: The aim of the study is to analyse whether air pollution and vehicular traffic exposure, during the first four years of life, influence obesity- related measures among 4 and 8-year-old children from a prospective birth cohort in Rome. METHODS: A cohort of newborns, enrolled in 2003-2004 within the GASPII project, was followed at 4 and 8 years of age with parental interviews and clinical examinations. Air pollution was assessed at residential address using Land Use Regression models (for NO2, NOx, PM10, PM2.5, PMcoarse, PM2.5 absorbance and one traffic variable (Total traffic load of all roads in a 100m buffer)). The outcomes under study were body mass index (BMI Z-scores according to WHO recommendations, considered both categorical and continuous) measured at 4 and 8 years, and, waist circumference, waist-to-hip ratio, total and HDL cholesterol measured at 8 years. The associations were evaluated through both cross-sectional and longitudinal approaches, using logistic regression models, Generalized Estimating Equation models (GEE) and linear regression models, as appropriate. Moreover, Inverse Probability Weighting (IPW) methodology was used to account for selection bias at enrolment and at follow-up. RESULTS: A total of 719 infants were enrolled and 581 (80.8%) and 499 (69.4%) were followed at 4 and 8 years, respectively. The prevalence of overweight/obesity was 9.3% and 36.9% at 4 and 8 years. No evidence of an association was found between vehicular traffic and being overweight/obese. Similarly, there was no evidence of an association between exposure to air pollutants and all other ponderal excess parameters. CONCLUSIONS: The study shows no association between exposure to vehicular traffic and exposure to pollutants on obesity related parameters such as BMI, blood lipids and abdominal adiposity during childhood. Overall evidence of air pollution being obesogenic remains limited.

[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.