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Background: Heat and cold are established environmental risk factors for human health. However, mapping the related health burden is a difficult task due to the complexity of the associations and the differences in vulnerability and demographic distributions. In this study, we did a comprehensive mortality impact assessment due to heat and cold in European urban areas, considering geographical differences and age-specific risks. Methods: We included urban areas across Europe between Jan 1, 2000, and Dec 12, 2019, using the Urban Audit dataset of Eurostat and adults aged 20 years and older living in these areas. Data were extracted from Eurostat, the Multi-country Multi-city Collaborative Research Network, Moderate Resolution Imaging Spectroradiometer, and Copernicus. We applied a three-stage method to estimate risks of temperature continuously across the age and space dimensions, identifying patterns of vulnerability on the basis of city-specific characteristics and demographic structures. These risks were used to derive minimum mortality temperatures and related percentiles and raw and standardised excess mortality rates for heat and cold aggregated at various geographical levels. Findings: Across the 854 urban areas in Europe, we estimated an annual excess of 203 620 (empirical 95% CI 180 882–224 613) deaths attributed to cold and 20 173 (17 261–22 934) attributed to heat. These corresponded to age-standardised rates of 129 (empirical 95% CI 114–142) and 13 (11–14) deaths per 100 000 person-years. Results differed across Europe and age groups, with the highest effects in eastern European cities for both cold and heat. Interpretation: Maps of mortality risks and excess deaths indicate geographical differences, such as a north–south gradient and increased vulnerability in eastern Europe, as well as local variations due to urban characteristics. The modelling framework and results are crucial for the design of national and local health and climate policies and for pr

Background: Evidence on the potential interactive effects of heat and ambient air pollution on cause-specific mortality is inconclusive and limited to selected locations. Objectives: We investigated the effects of heat on cardiovascular and respiratory mortality and its modification by air pollution during summer months (six consecutive hottest months) in 482 locations across 24 countries. Methods: Location-specific daily death counts and exposure data (e.g., particulate matter with diameters ≤ 2.5 µm [PM2.5]) were obtained from 2000 to 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted heat effects at low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th percentile of the location-specific pollutant concentrations. Country-specific and overall estimates were derived using a random-effects multilevel meta-analytical model. Results: Heat was associated with increased cardiorespiratory mortality. Moreover, the heat effects were modified by elevated levels of all air pollutants in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 7.7% (95% Confidence Interval [CI] 7.6–7.7), 11.3% (95%CI 11.2–11.3), and 14.3% (95% CI 14.1–14.5) at low, medium, and high levels of PM2.5, respectively. Similarly, cardiovascular mortality increased by 1.6 (95%CI 1.5–1.6), 5.1 (95%CI 5.1–5.2), and 8.7 (95%CI 8.7–8.8) at low, medium, and high levels of O3, respectively. Discussion: We observed considerable modification of the heat effects on cardiovascular and respiratory mortality by elevated levels of air pollutants. Therefore, mitigation measures following the new WHO Air Quality Guidelines are crucial to enhance better health and promote sustainable development. © 2023

Background: A growing body of evidence suggests that exposure to natural environments, such as green space, may have a beneficial role in health. However, there is limited evidence regarding the effects of exposure to blue spaces and mortality. We investigated the association of exposure to blue spaces with natural and cause-specific mortality in Greece using an ecological study design Methods: Mortality and socioeconomic data were obtained from 1,035 municipal units (MUs) from the 2011 census data. To define exposure to “blue” we used a rate of the land cover categories related to blue space from the COoRdination and INformation on the Environmental (CORINE) 2012 map per 10,000 persons in the municipal unit. We further assessed the exposure to blue space in the MUs that are located in the coastline of Greece using the distance to the coast as a proxy for proximity to blue space. the Annual PM2.5, NO2, BC and O3 concentrations for 2010 were predicted by land use regression models while the normalized difference vegetation index was used to assess greenness. We applied single and two exposure Poisson regression models accounting for spatial autocorrelation and adjusting for unemployment and lung cancer mortality rates, percentages of the population aged 25–64 with upper secondary or tertiary education attainment and of those born in Greece, and urbanicity. The analysis was conducted for the whole country and separately by varying geographical definitions. Results: An interquartile range (IQR) increase of blue space per 10,000 persons was associated with decreased risk in natural mortality (Relative Risk (RR): 0.98 (95% confidence interval (CI): 0.98, 0.99), as well as in mortality due to cardiovascular causes, respiratory causes and diseases of the nervous system 0.98 (95% CI: 0.97, 0.99); 0.97 (95% CI: 0.95, 0.99); 0.94 (95% CI: 0.88, 1.00) respectively). We estimated protective associations for ischemic heart disease (IHD) mortality (RR = 0.98, 95% CI: 0.97, 1.00 p

The authors would like to acknowledge the participation of 4 additional authors to this article. They contributed to the processing of the Japanese dataset used in the study. The corrected authorship, the corrected Acknowledgements and the corrected Contributors and Declaration of interests sections are presented below. H.M.C. and W.L. performed data analysis. W.L., D.R., A.U., A.E., A.M.V., A.Z., A.G., A.Z., A.T., B.A., B.F., C.Í., C.Å., C.F.S.N., E.I., E.L., F.M., F.A., F.S., H.O. H.K., J.K., J.M., J.S., J.J., K.K., M.H.D., M.S.R., M.H., M.P., N.R., N.S., S.O., S.T., X.S., Y.H., Y.K., YL.G., Y.G., and M.L.B. provided essential data resources. H.M.C. drafted the first version. H.M.C. and M.L.B. performed writing and editing the manuscript. H.M.C., W.L., A.U., A.G., A.T., B.A., E.L., F.S., S.T., and M.L.B. conducted reviewing. H.M.C. and D.R. have developed the figures. All authors have read and acknowledged the final manuscript. © 2022 The Author(s)

Rheumatoid arthritis (RA) is considered the most common form of autoimmune arthritis. The disease’s prevalence is around 0.5–1% worldwide, but it seems to vary among different populations. The aim of this study was to estimate the prevalence of self-reported diagnosed RA in the general adult population in Greece. The data were derived from the Greek Health Examination Survey EMENO, a population-based survey performed between 2013 and 2016. Of the 6006 participants (response rate 72%), 5884 were eligible for this study. Prevalence estimates were calculated according to the study design. Prevalence of self-reported RA was estimated to be overall 0.5% (95% CI 0.4–0.7) being approximately three times higher in women than in men (0.7% vs 0.2%, p value = 0.004). A decrease in the prevalence of RA was observed in urban areas of the country. In contrast, higher disease rates were reported in individuals with lower socioeconomic status. Multivariable regression analysis showed that gender, age, and income were related to the occurrence of the disease. Osteoporosis and thyroid disease were the two comorbidities observed at statistically significant higher rates in individuals with self-reported RA. The prevalence of self-reported RA in Greece is similar to that reported in other European countries. Gender, age, and income are the main factors related to the disease’s prevalence in Greece. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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

Background: The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Methods: Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants’ baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. Results: The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. Conclusions: We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after a

Ambient air pollution is an established risk factor for premature mortality from chronic cardiovascular, respiratory and metabolic diseases, while evidence on neurodegenerative diseases and psychiatric disorders remains limited. We examined the association between long-term exposure to air pollution and mortality from dementia, psychiatric disorders, and suicide in seven European cohorts. Within the multicenter project ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE), we pooled data from seven European cohorts from six countries. Based on the residential addresses, annual mean levels of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), ozone (O3), and 8 PM2.5 components were estimated using Europe-wide hybrid land-use regression models. We applied stratified Cox proportional hazard models to investigate the associations between air pollution and mortality from dementia, psychiatric disorders, and suicide. Of 271,720 participants, 900 died from dementia, 241 from psychiatric disorders, and 164 from suicide, during a mean follow-up of 19.7 years. In fully adjusted models, we observed positive associations of NO2 (hazard ratio [HR] = 1.38; 95 % confidence interval [CI]: 1.13, 1.70 per 10 µg/m3), PM2.5 (HR = 1.29; 95 % CI: 0.98, 1.71 per 5 µg/m3), and BC (HR = 1.37; 95 % CI: 1.11, 1.69 per 0.5 × 10−5/m) with psychiatric disorders mortality, as well as with suicide (NO2: HR = 1.13 [95 % CI: 0.92, 1.38]; PM2.5: HR = 1.19 [95 % CI: 0.76, 1.87]; BC: HR = 1.08 [95 % CI: 0.87, 1.35]), and no association with dementia mortality. We did not detect any positive associations of O3 and 8 PM2.5 components with any of the three mortality outcomes. Long-term exposure to NO2, PM2.5, and BC may lead to premature mortality from psychiatric disorders and suicide. © 2022

The original version of this Article contained an error in Affiliation 25, which was incorrectly given as ‘Faculty of Medicine ArqFuturo INSPER, University of São Paulo, São Paulo, Brazil’. The correct affiliation is listed below. Faculty of Medicine, University of São Paulo, São Paulo, Brazil The original Article has been corrected. © The Author(s) 2022.

Background: The association between long-term exposure to air pollution and mortality from cardiorespiratory diseases is well established, yet the evidence for other diseases remains limited. Objectives: To examine the associations of long-term exposure to air pollution with mortality from diabetes, dementia, psychiatric disorders, chronic kidney disease (CKD), asthma, acute lower respiratory infection (ALRI), as well as mortality from all-natural and cardiorespiratory causes in the Danish nationwide administrative cohort. Methods: We followed all residents aged ≥ 30 years (3,083,227) in Denmark from 1 January 2000 until 31 December 2017. Annual mean concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (warm season) were estimated using European-wide hybrid land-use regression models (100 m × 100 m) and assigned to baseline residential addresses. We used Cox proportional hazard models to evaluate the association between air pollution and mortality, accounting for demographic and socioeconomic factors. We additionally applied indirect adjustment for smoking and body mass index (BMI). Results: During 47,023,454 person-years of follow-up, 803,881 people died from natural causes. Long-term exposure to PM2.5 (mean: 12.4 µg/m3), NO2 (20.3 µg/m3), and/or BC (1.0 × 10-5/m) was statistically significantly associated with all studied mortality outcomes except CKD. A 5 µg/m3 increase in PM2.5 was associated with higher mortality from all-natural causes (hazard ratio 1.11; 95% confidence interval 1.09–1.13), cardiovascular disease (1.09; 1.07–1.12), respiratory disease (1.11; 1.07–1.15), lung cancer (1.19; 1.15–1.24), diabetes (1.10; 1.04–1.16), dementia (1.05; 1.00–1.10), psychiatric disorders (1.38; 1.27–1.50), asthma (1.13; 0.94–1.36), and ALRI (1.14; 1.09–1.20). Associations with long-term exposure to ozone (mean: 80.2 µg/m3) were generally negative but became significantly positive for several endpoints in two-pollutant mo

Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days’ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: −0.33 to 1.69), 1.34% (95% CI: −0.14 to 2.73), 1.99% (95% CI: 0.29–3.57), and 2.73% (95% CI: 0.76–4.50) of total deaths for Q1–Q4 (first quartile–fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25–9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: −0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health. © 2022 The Author(s)

Evidence for the association between long-term exposure to ambient particulate matter components and mortality from natural causes is sparse and inconsistent. We evaluated this association in six large administrative cohorts in the framework of the Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) project. We analyzed data from country-wide administrative cohorts in Norway, Denmark, the Netherlands, Belgium, Switzerland and in Rome (Italy). Annual 2010 mean concentrations of copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn) in fine particulate matter (PM2.5) were estimated using 100 × 100 m Europe-wide hybrid land use regression models assigned to the participants' residential addresses. We applied cohort-specific Cox proportional hazard models controlling for area- and individual-level covariates to evaluate associations with natural mortality. Two pollutant models adjusting for PM2.5 total mass or nitrogen dioxide (NO2) were also applied. We pooled cohort-specific estimates using a random effects meta-analysis. We included almost 27 million participants contributing more than 240 million person-years. All components except Zn were significantly associated with natural mortality [pooled Hazard Ratios (HRs) (95% CI): 1.037 (1.014, 1.060) per 5 ng/m3 Cu; 1.069 (1.031, 1.108) per 100 ng/m3 Fe; 1.039 (1.018, 1.062) per 50 ng/m3 K; 1.024 (1.006, 1.043) per 1 ng/m3 Ni; 1.036 (1.016, 1.057) per 200 ng/m3 S; 1.152 (1.048, 1.266) per 100 ng/m3 Si; 1.020 (1.006, 1.034) per 2 ng/m3 V]. Only K and Si were robust to PM2.5 or NO2 adjustment [pooled HRs (95% CI) per 50 ng/m3 in K: 1.025 (1.008, 1.044), 1.020 (0.999, 1.042) and per 100 ng/m3 in Si: 1.121 (1.039, 1.209), 1.068 (1.022, 1.117) adjusted for PM2.5 and NO2 correspondingly]. Our findings indicate an association of natural mortality with most components, which was reduced after adjustment for PM2.5 and especially NO2. © 2021

Long-term exposure to air pollution has been associated with increased natural-cause mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies have examined the potential synergistic effects of exposure to pollutants and greenness. We investigated the association between exposure to air pollution and greenness with nervous system related mortality, cardiometabolic and chronic obstructive pulmonary diseases (COPD) mortality in Greece, using an ecological study design. We collected socioeconomic and mortality data for 1035 municipal units from the 2011 Census. Annual PM2.5, NO2, BC and O3 concentrations for 2010 were predicted at 100 × 100 m grids by hybrid land use regression models. The normalized difference vegetation index (NDVI) was used for greenness. We applied single and two-exposure Poisson regression models on standardized mortality rates accounting for spatial autocorrelation. We assessed interactions between pollutants and greenness. An interquartile range increase in PM2.5, NO2 and BC was associated with increased risk in mortality from diseases of the nervous system (relative risk (RR): 1.14, 95% confidence interval (CI): 1.01, 1.28); 1.03 (95% CI: 0.99, 1.07); 1.05 (95% CI: 1.00, 1.10) respectively) and from cerebrovascular disease (RR: 1.14, 95% CI: 1.10, 1.18); 1.02 (95% CI: 1.01, 1.04); 1.02 (95% CI: 1.00, 1.04) respectively). PM2.5 was associated with ischemic heart disease mortality (RR: 1.05, 95% CI: 1.01, 1.10). We estimated inverse associations for all outcomes with O3 and for mortality from diseases of the nervous system or COPD with greenness. Estimates were mostly robust to co-exposure adjustment. Interactions were identified between NDVI and O3 or PM2.5 on mortality from the diseases of the nervous system, with higher effect estimates in greener areas. Our findings support the adverse effects of air pollution and the beneficial role of greenness on cardiovascular and nervous system related mortality. Furthe

Background: The association between fine particulate matter (PM2.5) and mortality widely differs between as well as within countries. Differences in PM2.5 composition can play a role in modifying the effect estimates, but there is little evidence about which components have higher impacts on mortality. Methods: We applied a 2-stage analysis on data collected from 210 locations in 16 countries. In the first stage, we estimated location-specific relative risks (RR) for mortality associated with daily total PM2.5 through time series regression analysis. We then pooled these estimates in a meta-regression model that included city-specific logratio-transformed proportions of seven PM2.5 components as well as meta-predictors derived from city-specific socio-economic and environmental indicators. Results: We found associations between RR and several PM2.5 components. Increasing the ammonium (NH₄⁺) proportion from 1% to 22%, while keeping a relative average proportion of other components, increased the RR from 1.0063 (95% confidence interval [95% CI] = 1.0030, 1.0097) to 1.0102 (95% CI = 1.0070, 1.0135). Conversely, an increase in nitrate (NO₃⁻) from 1% to 71% resulted in a reduced RR, from 1.0100 (95% CI = 1.0067, 1.0133) to 1.0037 (95% CI = 0.9998, 1.0077). Differences in composition explained a substantial part of the heterogeneity in PM2.5 risk. Conclusions: These findings contribute to the identification of more hazardous emission sources. Further work is needed to understand the health impacts of PM2.5 components and sources given the overlapping sources and correlations among many components.

Background: Increased mortality risk is associated with short-term temperature variability: However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° degrees from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1753392 deaths (95% CI 1159 901–2357 718) were associated with temperature variability per year, ac

By 2030, more than 80% of Europe's population will live in an urban environment. The urban exposome, consisting of factors such as where we live and work, where and what we eat, our social network, and what chemical and physical hazards we are exposed to, provides important targets to improve population health. The EXPANSE (EXposome Powered tools for healthy living in urbAN SEttings) project will study the impact of the urban exposome on the major contributors to Europe's burden of disease: Cardio-Metabolic and Pulmonary Disease. EXPANSE will address one of the most pertinent questions for urban planners, policy makers, and European citizens: "How to maximize one's health in a modern urban environment?" EXPANSE will take the next step in exposome research by (1) bringing together exposome and health data of more than 55 million adult Europeans and OMICS information for more than 2 million Europeans; (2) perform personalized exposome assessment for 5,000 individuals in five urban regions; (3) applying ultra-high-resolution mass-spectrometry to screen for chemicals in 10,000 blood samples; (4) evaluating the evolution of the exposome and health through the life course; and (5) evaluating the impact of changes in the urban exposome on the burden of cardiometabolic and pulmonary disease. EXPANSE will translate its insights and innovations into research and dissemination tools that will be openly accessible via the EXPANSE toolbox. By applying innovative ethics-by-design throughout the project, the social and ethical acceptability of these tools will be safeguarded. EXPANSE is part of the European Human Exposome Network. © 2021 Georg Thieme Verlag. All rights reserved.

The increasing number of human biomonitoring (HBM) studies undertaken in recent decades has brought to light the need to harmonise procedures along all phases of the study, including sampling, data collection and analytical methods to allow data comparability. The first steps towards harmonisation are the identification and collation of HBM methodological information of existing studies and data gaps. Systematic literature reviews and meta-analyses have been traditionally put at the top of the hierarchy of evidence, being increasingly applied to map available evidence on health risks linked to exposure to chemicals. However, these methods mainly capture peer-reviewed articles, failing to comprehensively identify other important, unpublished sources of information that are pivotal to gather a complete map of the produced evidence in the area of HBM. Within the framework of the European Human Biomonitoring Initiative (HBM4EU) initiative—a project that joins 30 countries, 29 from Europe plus Israel, the European Environment Agency and the European Commission—a comprehensive work of data triangulation has been made to identify existing HBM studies and data gaps across countries within the consortium. The use of documentary analysis together with an up-to-date platform to fulfil this need and its implications for research and practice are discussed. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Background: Epidemiological studies have documented the adverse effects of long-term exposure to fine particulate matter (PM2.5) on health, while there has been less research on the effects of nitrogen dioxide (NO2), black carbon (BC) and especially ozone (O3). Furthermore, there is limited evidence for the synergistic effects of exposure to pollutants and greenness. We investigated the association of long-term exposure to air pollution and greenness with natural-cause, cardiovascular and respiratory mortality in Greece using an ecological study design. Methods: Mortality and socioeconomic data were obtained from 1035 municipal units from the 2011 census data. Annual average PM2.5, NO2, BC and O3 concentrations for 2010 were derived from 100 × 100 m surfaces predicted by hybrid LUR models. The normalized difference vegetation index was used to assess greenness. We applied Poisson regression models on standardized mortality rates adjusted for socioeconomic indicators and lung cancer rates, accounting for spatial autocorrelation. The analysis was conducted initially for the whole country and then separately for urban and rural areas. We assessed interactions between pollutants and greenness and applied two-exposure models. Results: An interquartile range (IQR) increase in PM2.5, NO2 and BC was associated with increases in natural-cause mortality (Relative Risk (RR) 1.09, 95% confidence interval (CI): 1.08, 1.11; RR 1.03 (95% CI: 1.03, 1.04) and RR 1.02 (95% CI: 1.02, 1.03), respectively), while PM2.5 and NO2 were also associated with cause-specific mortality. Greenness was associated with lower natural-cause (RR 0.95, 95% CI: 0.94, 0.96 per IQR) and cause-specific mortality. For all outcomes we estimated a protective association with O3 (natural-cause mortality RR 0.79, 95% CI: 0.76, 0.82 per IQR). All associations were stronger in urban areas. We estimated negative statistically significant interactions between air pollution and greenness for respiratory morality and

Background: It is known that on days with high temperatures higher mortality is observed and there is a minimum mortality temperature (MMT) point which is higher in places with warmer climate. This indicates some population adaptation to local climate but information on how quickly this adaptation will occur under climate change is lacking. Methods: To investigate this, we associated daily mortality data with temperature during the warm period in 2004–2013 for London inhabitants born in five climatic zones (UK, Tropical, Sub-tropical, Boreal and Mixed). We fitted Poisson regression with distributed-lag non-linear models for each climatic zone group separately to estimate group-specific exposure-response associations and MMTs. We report relative risks of death comparing the 95th percentile (21 °C) and maximum (25 °C) of the temperature distribution in London with the zone-specific minimum mortality temperature. Results: No heat-related mortality was observed for people born in countries with Sub-tropical and Mixed climates. We observed an increase of 26%, 35% and 39% in the risk of death at 25 °C compared to the MMT in people born in the UK (marine climate), Tropical and Boreal climate respectively. The temperatures with the lowest mortality in these groups ranged from 15.9 to 17.7 °C. Discussion: Our findings imply that people born in different climatic zones do not adapt fully to their new environment within their lifetime. This implies that populations may not adapt readily to climate change and will suffer increased effects from heat. In the presence of climate change, policy makers should be aware of a delayed process of adaptation. © 2020

The aim of this study was to evaluate the longitudinal changes in alcohol consumption (total alcohol and types of alcoholic beverages) of the Greek EPIC cohort participants (28,572) during a 17-year period (1994–2011), with alcohol information being recorded repeatedly over time. Descriptive statistics were used to show crude trends in drinking behavior. Mixed-effects models were used to study the consumption of total alcohol, wine, beer and spirits/other alcoholic beverages in relation to birth cohort, socio-demographic, lifestyle and health factors. We observed a decreasing trend of alcohol intake as age increased, consistent for total alcohol consumption and the three types of beverages. Older birth cohorts had lower initial total alcohol consumption (8 vs. 10 g/day) and steeper decline in wine, spirits/other alcoholic beverages and total alcohol consumption compared to younger cohorts. Higher education and smoking at baseline had a positive association with longitudinal total alcohol consumption, up to +30% (vs. low education) and more than +25% (vs. non-smoking) respectively, whereas female gender, obesity, history of heart attack, diabetes, peptic ulcer and high blood pressure at baseline had a negative association of −85%, −25%, −16%, −37%, −22% and −24% respectively. Alcohol consumption changed over age with different trends among the studied subgroups and types of alcohol, suggesting targeted monitoring of alcohol consumption. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change. © 2021, The Author(s), under exclusive licence to Springer Nature Limited.

Background: Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale. Methods: We collected data from 658 communities in 43 countries under different climates. We estimated temperature-mortality associations to derive the MMT for each community using Poisson regression with distributed lag nonlinear models. We investigated the variation in MMT by climatic zone using a mixed-effects meta-analysis and explored the association with climatic and socioeconomic indicators. Results: The geographical distribution of MMTs varied considerably by country between 14.2 and 31.1 ºC decreasing by latitude. For climatic zones, the MMTs increased from alpine (13.0 ºC) to continental (19.3 ºC), temperate (21.7 ºC), arid (24.5 ºC), and tropical (26.5 ºC). The MMT percentiles (MMTPs) corresponding to the MMTs decreased from temperate (79.5th) to continental (75.4th), arid (68.0th), tropical (58.5th), and alpine (41.4th). The MMTs indreased by 0.8 ºC for a 1 ºC rise in a community's annual mean temperature, and by 1 ºC for a 1 ºC rise in its SD. While the MMTP decreased by 0.3 centile points for a 1 ºC rise in a community's annual mean temperature and by 1.3 for a 1 ºC rise in its SD. Conclusions: The geographical distribution of the MMTs and MMTPs is driven mainly by the mean annual temperature, which seems to be a valuable indicator of overall adaptation across populations. Our results suggest that populations have adapted to the average temperature, although there is still more room for adaptation. Copyright © 2021 The Authors.

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to

BACKGROUND: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤2:5 lm [fine particulate matter (PM2:5)] components and mortality have been reported, partly related to challenges in exposure assessment. OBJECTIVES: We investigated the associations between long-term exposure to PM2:5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2:5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms. METHODS: We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985–2005). Residential exposure to 2010 annual average concentration of eight PM2:5 components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a 100 × 100 m scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for PM2:5 mass and nitrogen dioxide (NO2) separately. RESULTS: We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both PM2:5 and NO2. HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR-and RF-modeled exposures, respectively, per 2 ng=m3, adjusting for PM2:5 mass. Associati

Background: Air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD), but evidence is sparse and inconsistent. Objectives: We examined the association between long-term exposure to low-level air pollution and COPD incidence. Methods: Within the ‘Effects of Low-Level Air Pollution: A Study in Europe’ (ELAPSE) study, we pooled data from three cohorts, from Denmark and Sweden, with information on COPD hospital discharge diagnoses. Hybrid land use regression models were used to estimate annual mean concentrations of particulate matter with a diameter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) in 2010 at participants’ baseline residential addresses, which were analysed in relation to COPD incidence using Cox proportional hazards models. Results: Of 98,058 participants, 4,928 developed COPD during 16.6 years mean follow-up. The adjusted hazard ratios (HRs) and 95% confidence intervals for associations with COPD incidence were 1.17 (1.06, 1.29) per 5 µg/m3 for PM2.5, 1.11 (1.06, 1.16) per 10 µg/m3 for NO2, and 1.11 (1.06, 1.15) per 0.5 10−5m−1 for BC. Associations persisted in subset participants with PM2.5 or NO2 levels below current EU and US limit values and WHO guidelines, with no evidence for a threshold. HRs for NO2 and BC remained unchanged in two-pollutant models with PM2.5, whereas the HR for PM2.5 was attenuated to unity with NO2 or BC. Conclusions: Long-term exposure to low-level air pollution is associated with the development of COPD, even below current EU and US limit values and possibly WHO guidelines. Traffic-related pollutants NO2 and BC may be the most relevant. © 2020

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

Background: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). Methods: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. Results: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates’ standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. Conclusions: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data. © 2021 The Authors

Introduction: To characterize air pollution exposure at a fine spatial scale, different exposure assessment methods have been applied. Comparison of associations with health from different exposure methods are scarce. The aim of this study was to evaluate associations of air pollution based on hybrid, land-use regression (LUR) and dispersion models with natural cause and cause-specific mortality. Methods: We followed a Dutch national cohort of approximately 10.5 million adults aged 29+ years from 2008 until 2012. We used Cox proportional hazard models with age as underlying time scale and adjusted for several potential individual and area-level socio-economic status confounders to evaluate associations of annual average residential NO2, PM2.5 and BC exposure estimates based on two stochastic models (Dutch LUR, European-wide hybrid) and deterministic Dutch dispersion models. Results: Spatial variability of PM2.5 and BC exposure was smaller for LUR compared to hybrid and dispersion models. NO2 exposure variability was similar for the three methods. Pearson correlations between hybrid, LUR and dispersion modeled NO2 and BC ranged from 0.72 to 0.83; correlations for PM2.5 were slightly lower (0.61–0.72). In general, all three models showed stronger associations of air pollutants with respiratory disease and lung cancer mortality than with natural cause and cardiovascular disease mortality. The strength of the associations differed between the three exposure models. Associations of air pollutants estimated by LUR were generally weaker compared to associations of air pollutants estimated by hybrid and dispersion models. For natural cause mortality, we found a hazard ratio (HR) of 1.030 (95% confidence interval (CI): 1.019, 1.041) per 10 µg/m3 for hybrid modeled NO2, a HR of 1.003 (95% CI: 0.993, 1.013) per 10 µg/m3 for LUR modeled NO2 and a HR of 1.015 (95% CI: 1.005, 1.024) per 10 µg/m3 for dispersion modeled NO2. Conclusion: Air pollution was positively associated with

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 modi

Objective: To evaluate the short term associations between nitrogen dioxide (NO₂) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design: Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting: 398 cities in 22 low to high income countries/regions. Main outcome measures: Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results: On average, a 10 μg/m³ increase in NO₂ concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM₁₀ and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO₂ concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions: This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO₂ and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO₂.