[Impact of heat and cold on cause -specific mortality in Italy]

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.

Assessment of short-term heat effects on cardiovascular mortality and vulnerability factors using small area data in Europe

BACKGROUND

Short-term associations between heat and cardiovascular disease (CVD) mortality have been examined mostly in large cities. However, different vulnerability and exposure levels may contribute to spatial heterogeneity. This study assessed heat effects on CVD mortality and potential vulnerability factors using data from three European countries, including urban and rural settings.

METHODS

We collected daily counts of CVD deaths aggregated at the small-area level in Norway (small-area level: municipality), England and Wales (lower super output areas), and Germany (district) during the warm season (May-September) from 1996 to 2018. Daily mean air temperatures estimated by spatial-temporal models were assigned to each small area. Within each country, we applied area-specific Quasi-Poisson regression using distributed lag nonlinear models to examine the heat effects at lag 0-1 days. The area-specific estimates were pooled by random-effects meta-analysis to derive country-specific and overall heat effects. We examined individual- and area-level heat vulnerability factors by subgroup analyses and meta-regression, respectively.

RESULTS

We included 2.84 million CVD deaths in analyses. For an increase in temperature from the 75th to the 99th percentile, the pooled relative risk (RR) for CVD mortality was 1.14 (95% CI: 1.03, 1.26), with the country-specific RRs ranging from 1.04 (1.00, 1.09) in Norway to 1.24 (1.23, 1.26) in Germany. Heat effects were stronger among women [RRs (95% CIs) for women and men: 1.18 (1.08, 1.28) vs. 1.12 (1.00, 1.24)]. Greater heat vulnerability was observed in areas with high population density, high degree of urbanization, low green coverage, and high levels of fine particulate matter.

CONCLUSION

This study provides evidence for the heat effects on CVD mortality in European countries using high-resolution data from both urban and rural areas. Besides, we identified individual- and area-level heat vulnerability factors. Our findings may facilitate the development of heat-health action plans to increase resilience to climate change.

[Acute effects of air pollution and extreme temperatures on cause-specific mortality in Italy. Results of the BIGEPI project.]

INTRODUCTION

Air pollution and extreme temperatures have been associated with multiple adverse health effects, especially on the cardiovascular and respiratory systems. The evidence of a relationship between daily exposures and mortality from metabolic, nervous and mental causes needs to be strengthened. The aim of this study is to investigate the association between daily exposure to fine particulate matter (PM2.5) and extreme temperatures (heat and cold) with cause-specific mortality in the entire Italian population.

METHODS

The daily counts of deaths from natural, cardiovascular, respiratory, metabolic, diabetes, nervous and mental causes were provided by Istat at the municipal level for the period 2006-2015. Through the application of machine-learning models based on satellite data and spatiotemporal variables, population-weighted exposures to daily mean PM2.5 (2013-2015) and air temperature (2006-2015) were estimated at municipality level. Time-series models adjusted for seasonal and long-term trends were applied, and associations between the above exposures and different causes of death at the national level were estimated.

RESULTS

The study found a marked effect of PM2.5 on deaths from nervous causes, with a % increase of risk (IR%) of 6.55% (95% confidence interval: 3.38%-9.81%) per PM2.5 increases of 10 µg/m3. The study also highlighted significant effects of low and high temperatures on all study outcomes. The effects were greater for high temperatures. In particular, the effects of heat, expressed as a % increase in risk per temperature increase from the 75th to the 99th percentile, show the highest associations with mortality from nervous causes (58.3%; 95%CI: 49.7%-67.5%), mental causes (48.4%; 95%CI: 40.4%-56.9%), respiratory causes 45.8%; 95%CI: 39.7%-52.1%) and metabolic causes (36.9%; 95%CI: 30.6%-43.5%).

DISCUSSION

The study showed a strong association between daily exposure to PM2.5 and extreme temperatures, especially heat, with mortality outcomes, especially those under-investigated, such as diabetes, metabolic, nervous and mental causes.

A spatial indicator of environmental and climatic vulnerability in Rome

BACKGROUND

Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies.

METHODS

From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km² in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM_2.5, PM₁₀, NO₂, C₆H₆, SO₂), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described.

RESULTS

The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO₂ in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index.

CONCLUSIONS

A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.

Impatto sanitario dell'inquinamento atmosferico e della temperatura dell'aria in Italia: evidenze per azioni concrete

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.

Gli indicatori di Lancet Countdown per l'Italia: monitorare i cambiamenti climatici e la salute

OBJECTIVES

to provide evidence of the health impacts of climate change in Italy.

DESIGN

descriptive study.

SETTING AND PARTICIPANTS

the indicators published in the 2022 Lancet Countdown report were adapted and refined to provide the most recent data relevant to Italy.

MAIN OUTCOME MEASURES

twelve indicators were measured, organized within five sections mirroring those of the 2022 Lancet Countdown report: climate change impacts, exposures, and vulnerabilities; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement.

RESULTS

the overall picture depicted by the analysis of the 12 indicators reveals two key findings. First, climate change is already affecting the health of Italian populations, with effects not being uniform across the Country and with the most vulnerable groups being disproportionately at risk. Second, results showed that Italy's mitigation response has been partial, with major costs to human health. Accelerated climate change mitigation through energy system decarbonisation and shifts to more sustainable modes of transport could offer major benefits to health from cleaner air locally and from more active lifestyles, and to climate change from reduction of global warming. The decarbonisation of agricultural systems would similarly offer health co-benefits to Italian population. Conclusions: through accelerated action on climate change mitigation, Italy has the opportunity of delivering major and immediate health benefits to its population. Developing a key set of local indicators to monitor the impacts of climate change and evaluate response actions, in terms of adaptation and mitigation, can help support and enhance policy and action to fight climate changes.

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

BACKGROUND/AIM

Extreme temperatures have impact on the health and occupational injuries. The construction sector is particularly exposed. This study aims to investigate the association between extreme temperatures and occupation injuries in this sector, getting an insight in the main accidents-related parameters.

METHODS

Occupational injuries in the construction sector, with characteristic of accidents, were retrieved from Italian compensation data during years 2014-2019. Air temperatures were derived from ERA5-land Copernicus dataset. A region based time-series analysis, in which an over-dispersed Poisson generalized linear regression model, accounting for potential non-linearity of the exposure- response curve and delayed effect, was applied, and followed by a meta-analysis of region-specific estimates to obtain a national estimate. The relative risk (RR) and attributable cases of work-related injuries for an increase in mean temperature above the 75th percentile (hot) and for a decrease below the 25th percentile (cold) were estimated, with effect modifications by different accidents-related parameters.

RESULTS

The study identified 184,936 construction occupational injuries. There was an overall significant effect for high temperatures (relative risk (RR) 1.216 (95% CI: (1.095-1.350))) and a protective one for low temperatures (RR 0.901 (95% CI: 0.843-0.963)). For high temperatures we estimated 3,142 (95% CI: 1,772-4,482) attributable cases during the studied period. RRs from 1.11 to 1.30 were found during heat waves days. Unqualified workers, as well as masons and plumbers, were found to be at risk at high temperatures. Construction, quarry and industrial sites were the risky working environments, as well as specific physical activities like working with hand-held tools, operating with machine and handling of objects. Contact with sharp, pointed, rough, coarse 'Material Agent' were the more risky mode of injury in hot conditions.

CONCLUSIONS

Prevention policies are needed to reduce the exposure to high temperatures of construction workers. Such policies will become a critical issue considering climate change.

A nationwide study of air pollution from particulate matter and daily hospitalizations for respiratory diseases in Italy

BACKGROUND/AIM

The relationship between air pollution and respiratory morbidity has been widely addressed in urban and metropolitan areas but little is known about the effects in non-urban settings. Our aim was to assess the short-term effects of PM10 and PM2.5 on respiratory admissions in the whole country of Italy during 2006-2015.

METHODS

We estimated daily PM concentrations at the municipality level using satellite data and spatiotemporal predictors. We collected daily counts of respiratory hospital admissions for each Italian municipality. We considered five different outcomes: all respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), lower and upper respiratory tract infections (LRTI and URTI). Meta-analysis of province-specific estimates obtained by time-series models, adjusting for temperature, humidity and other confounders, was applied to extrapolate national estimates for each outcome. At last, we tested for effect modification by sex, age, period, and urbanization score. Analyses for PM_2.5 were restricted to 2013-2015 cause the goodness of fit of exposure estimation.

RESULTS

A total of 4,154,887 respiratory admission were registered during 2006-2015, of which 29% for LRTI, 12% for COPD, 6% for URTI, and 3% for asthma. Daily mean PM₁₀ and PM_2.5 concentrations over the study period were 23.3 and 17 μg/m³, respectively. For each 10 μg/m³ increases in PM₁₀ and PM_2.5 at lag 0-5 days, we found excess risks of total respiratory diseases equal to 1.20% (95% confidence intervals, 0.92, 1.49) and 1.22% (0.76, 1.68), respectively. The effects for the specific diseases were similar, with the strongest ones for asthma and COPD. Higher effects were found in the elderly and in less urbanized areas.

CONCLUSIONS

Short-term exposure to PM is harmful for the respiratory system throughout an entire country, especially in elderly patients. Strong effects can be found also in less urbanized areas.

Association between air temperature, air pollution and hospital admissions for pulmonary embolism and venous thrombosis in Italy

BACKGROUND

Previous studies reported a link between short-term exposure to environmental stressors (air pollution and air temperature) and atherothrombotic cardiovascular diseases. However, only few of them reported consistent associations with venous thromboembolism (VTE). Our aim was to estimate the association between daily air temperature and particulate matter (PM) air pollution with hospital admissions for pulmonary embolism (PE) and venous thrombosis (VT) at national level in Italy.

METHODS

We collected daily hospital PE and VT admissions from the Italian Ministry of Health during 2006-2015 in all the 8,084 municipalities of Italy, and we merged them with air temperature and daily PM10 concentrations estimated by satellite-based spatiotemporal models. First, we applied multivariate Poisson regression models at province level. Then, we obtained national overall effects by random-effects meta-analysis.

RESULTS

This analysis was conducted on 219,952 PE and 275,506 VT hospitalizations. Meta-analytical results showed weak associations between the two exposures and the study outcomes in the full year analysis. During autumn and winter, PE hospital admissions increased by 1.07% (95% confidence intervals [CI]: 0.21%; 1.92%) and 0.96% (95% CI: 0.07%; 1.83%) respectively, per 1 °C decrement of air temperature in the previous 10 days (lag 0-10). In summer we observed adverse effects at high temperatures, with a 1% (95% CI: 0.10%; 1.91%) increasing risk per 1 °C increment. We found no association between VT and cold temperatures.

CONCLUSION

Results show a significant effect of air temperature on PE hospitalizations in the cold seasons and summer. No effect of particulate matter was detected.

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.

A systematic review on the association between total and cardiopulmonary mortality/morbidity or cardiovascular risk factors with long-term exposure to increased or decreased ambient temperature

The health effects of acute exposure to temperature extremes are established; those of long-term exposure only recently received attention. We performed a systematic review to assess the associations of long-term (>3 months) exposure to higher or lower temperature on total and cardiopulmonary mortality and morbidity, screening 3455 studies and selecting 34. The studies were classified in those observing associations within a population over years with changing annual temperature indices and those comparing areas with a different climate. We also assessed the risk of bias, adapting appropriately an instrument developed by the World Health Organization for air pollution. Studies reported that annual temperature indices for extremes and variability were associated with annual increases in mortality, indicating that effects of temperature extremes cannot be attributed only to short-term mortality displacement. Studies on cardiovascular mortality indicated stronger associations with cold rather than hot temperature, whilst those on respiratory outcomes reported effects of both heat and cold but were few and used diverse health outcomes. Interactions with air pollution were not generally assessed. The few studies investigating effect modification showed stronger effects among the elderly and those socially deprived. Comparisons of health outcome prevalence between areas reported lower blood pressure and a tendency for higher obesity in populations living in warmer climates. Our review indicated interesting associations between long-term exposure to unusual temperature levels in specific areas and differences in health outcomes and cardiovascular risk factors between geographical locations with different climate, but the number of studies by design and health outcome was small. Risk of bias was identified because of the use of crude exposure assessment and inadequate adjustment for confounding. More and better designed studies, including the investigation of effect modifiers, are needed.

Excess mortality during the COVID-19 outbreak in Italy: a two-stage interrupted time-series analysis

Background

Italy was the first country outside China to experience the impact of the COVID-19 pandemic, which resulted in a significant health burden. This study presents an analysis of the excess mortality across the 107 Italian provinces, stratified by sex, age group and period of the outbreak.

Methods

The analysis was performed using a two-stage interrupted time-series design using daily mortality data for the period January 2015–May 2020. In the first stage, we performed province-level quasi-Poisson regression models, with smooth functions to define a baseline risk while accounting for trends and weather conditions and to flexibly estimate the variation in excess risk during the outbreak. Estimates were pooled in the second stage using a mixed-effects multivariate meta-analysis.

Results

In the period 15 February–15 May 2020, we estimated an excess of 47 490 [95% empirical confidence intervals (eCIs): 43 984 to 50 362] deaths in Italy, corresponding to an increase of 29.5% (95% eCI: 26.8 to 31.9%) from the expected mortality. The analysis indicates a strong geographical pattern, with the majority of excess deaths occurring in northern regions, where few provinces experienced increases up to 800% during the peak in late March. There were differences by sex, age and area both in the overall impact and in its temporal distribution.

Conclusion

This study offers a detailed picture of excess mortality during the first months of the COVID-19 pandemic in Italy. The strong geographical and temporal patterns can be related to the implementation of lockdown policies and multiple direct and indirect pathways in mortality risk.

Short-term effects of particulate matter on cardiovascular morbidity in Italy: a national analysis

AIMS

We aimed at investigating the relationship between particulate matter (PM) and daily admissions for cardiovascular diseases (CVDs) at national level in Italy.

METHODS AND RESULTS

Daily numbers of cardiovascular hospitalizations were collected for all 8084 municipalities of Italy, in the period 2013-2015. A satellite-based spatiotemporal model was used to estimate daily PM10 (inhalable particles) and PM2.5 (fine particles) concentrations at 1-km2 resolution. Multivariate Poisson regression models were fit to estimate the association between daily PM and cardiovascular admissions. Flexible functions were estimated to explore the shape of the associations at low PM concentrations, also in non-urban areas. We analysed 2 154 810 acute hospitalizations for CVDs (25% stroke, 24% ischaemic heart diseases, 22% heart failure, and 5% atrial fibrillation). Relative increases of total cardiovascular admissions, per 10 µg/m3 variation in PM10 and PM2.5 at lag 0-5 (average of last 6 days since admission), were 0.55% (95% confidence intervals: 0.32%, 0.77%) and 0.97% (0.67%, 1.27%), respectively. The corresponding estimates for heart failure were 1.70% (1.28%, 2.13%) and 2.66% (2.09%, 3.23%). We estimated significant effects of PM10 and PM2.5 also on ischaemic heart diseases, myocardial infarction, atrial fibrillation, and ischaemic stroke. Associations were similar between less and more urbanized areas, and persisted even at low concentrations, e.g. below WHO guidelines.

CONCLUSION

PM was robustly associated with peaks in daily cardiovascular admissions, especially for heart failure, both in large cities and in less urbanized areas of Italy. Current WHO Air Quality Guidelines for PM10 and PM2.5 are not sufficient to protect public health.

Excess all-cause mortality during the COVID-19 pandemic in Europe - preliminary pooled estimates from the EuroMOMO network, March to April 2020

A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March–April 2020. Excess mortality particularly affected  ≥ 65 year olds (91% of all excess deaths), but also 45–64 (8%) and 15–44 year olds (1%). No excess mortality was observed in 0–14 year olds.

Estimation of daily PM10 and PM2.5 concentrations in Italy, 2013-2015, using a spatiotemporal land-use random-forest model

Particulate matter (PM) air pollution is one of the major causes of death worldwide, with demonstrated adverse effects from both short-term and long-term exposure. Most of the epidemiological studies have been conducted in cities because of the lack of reliable spatiotemporal estimates of particles exposure in nonurban settings. The objective of this study is to estimate daily PM₁₀ (PM < 10 μm), fine (PM < 2.5 μm, PM_2.5) and coarse particles (PM between 2.5 and 10 μm, PM_2.5-10) at 1-km² grid for 2013-2015 using a machine learning approach, the Random Forest (RF). Separate RF models were defined to: predict PM_2.5 and PM_2.5-10 concentrations in monitors where only PM₁₀ data were available (stage 1); impute missing satellite Aerosol Optical Depth (AOD) data using estimates from atmospheric ensemble models (stage 2); establish a relationship between measured PM and satellite, land use and meteorological parameters (stage 3); predict stage 3 model over each 1-km² grid cell of Italy (stage 4); and improve stage 3 predictions by using small-scale predictors computed at the monitor locations or within a small buffer (stage 5). Our models were able to capture most of PM variability, with mean cross-validation (CV) R² of 0.75 and 0.80 (stage 3) and 0.84 and 0.86 (stage 5) for PM₁₀ and PM_2.5, respectively. Model fitting was less optimal for PM_2.5-10, in summer months and in southern Italy. Finally, predictions were equally good in capturing annual and daily PM variability, therefore they can be used as reliable exposure estimates for investigating long-term and short-term health effects.

[Big data in environmental epidemiology. Satellite and land use data for the estimation of environmental exposures at national level]

OBJECTIVES

to define a national geographic domain, with high spatial (1 km²) and temporal (daily) resolution, and to build a list of georeferenced environmental and temporal indicators useful for environmental epidemiology applications at national level.

DESIGN

geographic study.

SETTING AND PARTICIPANTS

study domain: Italian territory divided into 307,635 1-km² grid cells; study period: 2006-2012, divided into 2,557 daily time windows.

MAIN OUTCOME MEASURES

for each grid cell and day, an extensive number of indicators has been computed. These indicators include spatial (administrative layers, resident population, presence of water bodies, climatic zones, land use variables, impervious surfaces, orography, viability, point and areal emissions of air pollutants) and spatio-temporal predictors (particulate matter data from monitoring stations, meteorological parameters, desert dust advection episodes, aerosol optical depth, normalized difference vegetation index, planetary boundary layer) potentially useful to characterize population environmental exposures and to estimate their health effects, at national level.

RESULTS AND CONCLUSIONS

this study represents the first example of relational big data in environmental epidemiology at national level, where multiple sources of data (satellite, environmental, meteorology, land use, population) have been linked on a common spatial and temporal domain, aimed at promoting environmental epidemiology applications at national and local level.

[On the increase in mortality in Italy in 2015: analysis of seasonal mortality in the 32 municipalities included in the Surveillance system of daily mortality]

INTRODUCTION

the Italian National Institute of Statistics (Istat) estimated an increase in mortality in Italy of 11.3% between January and August 2015 compared to the previous year. During summer 2015, an excess in mortality, attributed to heat waves, was observed.

OBJECTIVES

to estimate the excess mortality in 2015 using data from the rapid mortality surveillance system (SiSMG) operational in 32 Italian cities.

DESIGN

time series models were used to estimate the excess in mortality among the elderly (65+ years) in 2015 by season (winter and summer). Excess mortality was defined as the difference between observed daily and expected (baseline) mortality for the five previous years (2009- 2013); seasonal mortality in 2015 was compared with mortality observed in 2012, 2013, and 2014. An analysis by cause of death (cardiovascular and respiratory), gender, and age group was carried out in Rome.

RESULTS

data confirm an overall estimated excess in mortality of +11% in 2015. Seasonal analysis shows a greater excess in winter (+13%) compared to the summer period (+10%). The excess in winter deaths seems to be attributable to the peak in influenza rather than to low temperatures. Summer excess mortality was attributed to the heat waves of July and August 2015. The lower mortality registered in Italy during summer 2014 (-5.9%) may have contributed to the greater excess registered in 2015. In Rome, cause-specific analysis showed a higher excess among the very old (85+ years) mainly for cardiovascular and respiratory causes in winter. In summer, the excess was observed among both the elderly and in the adult population (35-64 years).

CONCLUSION

results suggest the need for a more timely use of mortality data to evaluate the impact of different risk factors. Public health measures targeted to susceptible subgroups should be enhanced (e.g., Heat Prevention Plans, flu vaccination campaigns).

Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM₁₀ measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM₁₀ concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM₁₀=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM₁₀ levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM₁₀ concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data.