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A limited number of studies have addressed environmental inequality, using various study designs and methodologies and often reaching contradictory results. Following a standardized multi-city data collection process within the European project EURO-HEALTHY, we conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO 2), as a surrogate for traffic related air pollution, and ten socioeconomic indicators at local administrative unit level in nine European Metropolitan Areas. We applied mixed models for the associations under investigation with random intercepts per Metropolitan Area, also accounting for the spatial correlation. The stronger associations were observed between NO 2 levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of increasing concentrations with increasing levels of the indicators. Specifically, the highest vs the lowest quartile of each indicator above was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO 2 respectively. The association with population density most probably reflects the higher volume in vehicular traffic, which is the main source of NO 2 in urban areas. Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population. Image 1 • We investigated NO 2 associations with socioeconomic indicators in 9 European cities. • Higher NO 2 was observed in areas with higher population density. • Higher NO 2 was observed in areas with higher population born outside EU. • Higher NO 2 was observed in areas with higher crime or unemployment rates. • Worse air quality is typically encountered in deprived European urban areas. [ABSTRACT FROM AUTHOR]

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO 2 , O 3 and PM 2.5 with all-cause mortality, and PM 2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09). [Display omitted] • Regional heterogeneity occurred between all-cause mortality and NO 2 , O 3 and PM 2.5. • Sub-group/meta-regression analyses are less biased than a global meta-analysis. • Meta-regression has good specificity but poor sensitivity to detect heterogeneity. [ABSTRACT FROM AUTHOR]

The aim of this study is to estimate the mortality burden attributable to low temperature in Athens, Lisbon and London from 2002 to 2011 and to discuss related inequalities in socioeconomic conditions. We address a lack of quantitative estimates of cold-related mortality, particularly for the cities of Lisbon and Athens. To estimate the mortality burden attributable to low temperature, time-series regression analyses were carried out on daily mortality with respect to daily mean temperature for the three metropolitan areas to estimate the relative risk associated with a decrease in temperature. The number of cold-related deaths was estimated using the population Attributable Fraction. Lisbon presents higher relative risk (RR) than London and Athens; the RR for Athens is lower than for London. The coldrelated death rate is higher in Lisbon (53.2 deaths per 100,000 inhabitants) than in Athens (32.6) and London (37.6). The spatial heterogeneity between the three metropolitan areas in the risk estimates and cold-related mortality may result from the significant disparities in the built environment. Adequate public health planning and preventive measures in the built environment may help reduce cold-related deaths and decrease vulnerability to cold in European cities. • Cold has significant impacts on human health. • Cold-related death rate is higher in Lisbon than in Athens and London. • Spatial heterogeneity to cold may result from the built environment characteristics. • Preventive measures may help to reduce cold-related deaths and vulnerability. [ABSTRACT FROM AUTHOR]