We studied the potential synergy between air pollution and meteorology and their impact on mortality in nine European cities with data from 2004 to 2010. We used daily series of Apparent Temperature (AT), measurements of particulate matter (PM₁₀), ozone (O₃), and nitrogen dioxide (NO₂) and total non-accidental, cardiovascular, and respiratory deaths. We applied Poisson regression for city-specific analysis and random effects meta-analysis to combine city-specific results, separately for the warm and cold seasons. In the warm season, the percentage increase in all deaths from natural causes per °C increase in AT tended to be greater during high ozone days, although this was only significant for all ages when all causes were considered. On low ozone days, the increase in the total daily number of deaths was 1.84% (95% CI 0.87, 2.82), whilst it was 2.20% (95% CI 1.28, 3.13) in the high ozone days per 1 °C increase in AT. Interaction with PM₁₀ was significant for cardiovascular (CVD) causes of death for all ages (2.24% on low PM₁₀ days (95% CI 1.01, 3.47) whilst it is 2.63% (95% CI 1.57, 3.71) on high PM₁₀ days) and for ages 75+. In days with heat waves, no consistent pattern of interaction was observed. For the cold period, no evidence for synergy was found. In conclusion, some evidence of interactive effects between hot temperature and the levels of ozone and PM₁₀ was found, but no consistent synergy could be identified during the cold season.

The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM₁₀), PM ≤ 2.5 μm (PM_2.5), nitrogen dioxide (NO₂), and ozone (O₃) from 620 cities in 36 countries in the period 1995-2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. We analyzed 22,630,598 deaths. An increase in mean temperature from the 75^th to the 99^th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM₁₀ was equal to 10 or 90 μg/m³, respectively. Corresponding estimates when daily O₃ concentrations were 40 or 160 μg/m³ were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 μg/m³ increment in PM₁₀ was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1^st and 99^th city-specific percentiles, respectively. Corresponding mortality estimate for O₃ across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM_2.5 and NO₂. Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.

The European project PHASE aims to evaluate patterns of change in the temperature–mortality relationship and in the number of deaths attributable to heat in nine European cities in two periods, before and after summer 2003 (1996–2002 and 2004–2010). We performed age-specific Poisson regression models separately in the two periods, controlling for seasonality, air pollution and time trends. Distributed lag non-linear models were used to estimate the Relative Risks of daily mortality for increases in mean temperature from the 75th to 99th percentile of the summer distribution for each city. In the recent period, a reduction in the mortality risk associated to heat was observed only in Athens, Rome and Paris, especially among the elderly. Furthermore, in terms of heat-attributable mortality, 985, 787 and 623 fewer deaths were estimated, respectively, in the three cities. In Helsinki and Stockholm, there is a suggestion of increased heat effect. Noteworthy is that an effect of heat was still present in the recent years in all cities, ranging from +11% to +35%. In Europe, considering the warming observed in recent decades and population ageing, effective intervention measures should be promoted across countries, especially targeting vulnerable subgroups of the population with lower adaptive resources.

Understanding the dynamics of the temperature-mortality relationship is an asset to support public health interventions. We investigated the lag structure of the mortality response to cold and warm temperatures in 18 French cities between 2000 and 2010. A distributed lag non-linear generalized model using a quasi-Poisson distribution and controlling for classical confounding factors was built in each city. A fitted meta-analytical model combined the city-specific models to derive the best linear unbiased prediction of the association, and a meta-regression explored the influence of background characteristics of the cities. The fraction of mortality attributable to cold and heat was estimated with reference to the minimum mortality temperature. Between 2000 and 2010, 3.9% [CI 95% 3.2:4.6] of the total mortality was attributed to cold, and 1.2% [1.1:1.2] to heat. The immediate increase in mortality following high temperatures was partly compensated by a harvesting effect when temperatures were below the 99.2 percentiles of the mean temperature distributions. Cold represents a significant public health burden, mostly driven by moderate temperatures (between percentiles 2.5 and 25). The population is better adapted to warm temperatures, up to a certain intensity when heat becomes an acute environmental health emergency (above percentile 99). The rapid increase in mortality risk at very high temperatures percentiles calls for an active adaptation in a context of climate change.

Adapting the urban environment to heat is a public health priority in the context of climate change. Cities are now considering interventions on specific urban characteristics known to contribute to the urban heat island (UHI) such as vegetation and imperviousness. To explore how these urban characteristics influence the temperature-mortality relationship in the Paris region. We modeled the temperature-mortality relationship for the 1300 municipalities of the region from 1990 to 2015, while including an interaction with indicators that summarize the municipalities' main urban characteristics. Four indicators were tested: lack of green spaces, lack of trees, proportion of impervious surface, and overexposed population to a potential night UHI. The shape of the temperature-mortality relationship was similar across all municipalities, but with a higher slope at the highest temperatures in municipalities with less green spaces, less trees, and more impervious soil. For instance, in Paris and its close suburbs, the relative risk associated with a temperature in the 99th percentile of the temperature distribution (compared to the 50th percentile) was 2.17 [IC95% 1.98:2.38] in municipalities with 40% of their surface covered by trees compared to 2.57 [IC 95% 2.47:2.68] in municipalities with only 3% of their surface covered by trees. A lack of vegetation and a high degree of imperviousness were associated with a higher risk of heat-related mortality in the Paris region. Therefore, we can assume that interventions targeting these characteristics could reduce the health impacts of extreme heat. Such interventions should be coupled with other initiatives such as protecting the most vulnerable and promoting appropriate behaviors.