Background: Air pollution has been associated with adverse birth outcomes, but few studies have evaluated pregnancy loss, and none at a nationwide level. We evaluated prenatal PM2·5 exposure and pregnancy loss using live birth-identified conceptions (LBIC) as a proxy to identify critical windows of susceptibility. Methods: We conducted a nationwide time series study using a novel approach based on LBICs derived from administrative birth data from Spain between 2003 and 2017. We applied a two-stage modeling approach. Location-specific quassi-Poisson regression models combined with distributed lag nonlinear models were fitted, adjusting for temperature and temporal trends. Location-specific estimates were pooled using a multivariate mixed-effects meta-analysis. We further applied g-computation models to estimate the number of lost pregnancies attributable to PM2·5 exposure. Findings: Prenatal exposure to PM2·5 during gestational weeks 6 to 21 was associated with a decrease in LBIC counts (RR per 10 µg/m3: 0·92, 95% CI: 0·87, 0·96). In g-computation analyses, the largest week-specific estimate was observed around gestational week 12, where a 5 µg/m3 increase in PM2·5 was associated with 49·1 (95% CI: 12·2, 129·6) additional pregnancy losses per conception week. The cumulative estimate across the window of susceptibility was 561·8 (95% CI 158·7, 1,277) additional pregnancy losses per conception week. Interpretation: Our findings showed that prenatal PM2·5 exposure was associated with reduced LBIC counts, consistent with increased pregnancy loss risk during weeks 6 to 21. These findings have important implications for both pregnant individuals and fetal health, highlight the importance of reducing air pollution exposure during early-to-mid pregnancy.

While the long-term health impacts of air pollution are well documented, the combined short-term mortality burden of multiple pollutants at the continental scale remains insufficiently quantified. Previous assessments typically assume uniform risks, overlooking geographic and demographic heterogeneity in vulnerability. Here using daily mortality and exposure data from 653 regions across 31 countries (2003–2019), acute exposures to fine particles (PM2.5), coarse particles, nitrogen dioxide (NO2) and ozone are each significantly associated with a 0.54–1.14% increase in mortality risk per 10 μg m−3. The multi-pollutant model estimates 146,517 annual premature European deaths (95% confidence interval 119,992–173,771) attributable to their joint short-term effects. Vulnerability is not uniform: younger males face higher mortality risk from particulate matter and NO2 than young females, whereas risks increase with age among elderly females. Uniform risk models underestimate burden in Eastern and Southeastern Europe. These findings reveal substantial geographic and demographic inequities in pollution-related mortality, with direct implications for air quality policy and public health early-warning systems. Short-term exposure to the air pollutants PM2.5, PM10, nitrogen dioxide and ozone was associated with increased mortality in an analysis of 88.8 million deaths in 653 European regions, with differences between sexes and countries.

Numerous epidemiological studies have shown that non-optimal temperatures and acute respiratory infections (ARIs) contribute to increased mortality. The effect of temperature on mortality is typically estimated using splines of time, which are designed to account for seasonal and longer-term trends, and account for the potential unmeasured confounding, such as the seasonal effect of ARIs. However, the distinct impact of ARIs on mortality, as well as the direct effect of temperature on mortality that is not mediated via ARIs, remains insufficiently understood. This study investigates and quantifies the impact of ARIs on mortality, and the impact of temperature on mortality that is not mediated via ARIs. We used 38-year time-series data from the Czech Republic and applied a distributed lag non-linear model (DLNM) with one and multiple cross-bases to isolate the direct pathways of temperature and ARIs. Our approach allowed us to estimate the fraction of mortality attributable to each factor, providing a clearer understanding of their respective contributions to seasonal mortality patterns. Our findings indicate that ARI activity is a significant mediator of the relationship between temperature and mortality. Since low temperatures increase the risk of both cold-related mortality and ARI incidence, our results indicate that approximately 12% of cold-related deaths during the study period could be attributed to ARI activity. Additionally, an analysis of temporal changes in the combined effect of ARIs and temperature suggested that while the mediating role of ARIs on temperature-related mortality has weakened, the proportion of cold-attributable mortality has remained constant throughout the study period. Our findings are important for understanding both historical trends and future projections of seasonal mortality patterns. They highlight the need for further research on the roles of climatic and individual risk factors in long-term changes in temperature-related mortality, particularly considering the mediating role of ARIs.

Although heat exposure has been associated with higher gestational diabetes (GD) risk, few studies have employed statistical approaches that estimate the cumulative risk of multi-day exposure, and socioeconomic disparities of heat-related GD remain unexplored. We conducted a time-series study in the Barcelona metropolitan area to evaluate the association between cumulative temperature exposure and GD risk. Temperature data from the Meteorological Service of Catalonia were linked to the Information System for Research in Primary Care, with 8,796 GD cases registered between 2011 and 2022. Distributed lag nonlinear models were applied to estimate 30-day temperature effects on GD risk, and models were stratified by neighbourhood deprivation index. Cumulative exposure to high temperatures was associated with a twofold increased risk of GD. Individuals living in the most socioeconomically deprived areas showed higher heat-related GD risk. Given the projected increase in urban temperatures across the Mediterranean region, the health consequences of GD and the observed social disparities, public health policies that prioritize equity and climate resilience are needed to protect pregnant populations. Pregnant women exposed to cumulative days of high temperature saw a twofold-increased risk of gestational diabetes in a time-series study of 8,796 such cases in Barcelona between 2011 and 2022.

Marked socioeconomic divides and unequal advances in renewable energy transition across Europe have raised concerns about widening inequalities in air pollution exposure and related health risks. Here we analyzed 88.8 million deaths across 653 contiguous regions in 31 European countries, encompassing the entire urban and rural population of 521 million people from 2003 to 2019, to investigate how socioeconomic conditions and renewable energy adoption relate to regional disparities in acute air pollution-related mortality risks and their trends over time. Regions with higher gross domestic product per capita, lower poverty rates and longer life expectancy-primarily in Western and Northern Europe-showed lower and declining risks in air pollution-related mortality compared to other regions in Europe. We assessed renewable energy transition as both an upstream driver and an effect modifier of the relationship between air pollution and mortality. As an upstream driver, greater renewable energy adoption was associated with 15-54% lower air pollutant levels and, consequently, 12-53% fewer attributable deaths. As an effect modifier, high renewable adoption was significantly associated with lower and declining mortality risks. Taken together, our findings show that differences in socioeconomic conditions and energy transition are associated with widening disparities in air pollution-related health risks across Europe.

Although tools for climate change adaptation have proliferated, there is relatively little evidence about who they are intended to serve and how well they are suited to respond to decision contexts. We synthesized an inventory of 122 tools and found that around 73% of these are relevant to adaptation in the Mediterranean. We then examined who they are designed for, what they support, and how well they are suited to respond to decision contexts. We argue that access is not the main challenge, but alignment is. The results show that tools operate in isolation, often bound to administrative rather than physical boundaries, and provide limited guidance for choosing appropriate applications. Multilingual support and pathways to integrate local data are uneven. We outline actionable directions to improve this developing ecosystem, including linking tools to each other and to planning processes, making assumptions explicit, and involving anticipated users in the design process. These steps can turn a large and growing supply of tools into a more coherent, context-aware, and usable resource for adaptation and planning across the Mediterranean. Climate change adaptation tools in Mediterranean regions often fail the people and places that need them most, because they remain expert-oriented, administratively bounded, and poorly matched to regional realities, according to systematic evaluations.

Cities are vulnerable to heat-related health impacts due to the compounding effects of urban heat island (UHI) and rising temperatures because of climate change. Here we characterise the contextual factors exacerbating and attenuating the risk of mortality associated with high temperature in the city of Paris. Findings suggest that reducing urban heat and mitigating UHI through urban greening should be at the forefront of adaptation strategies to prevent heat-related health impacts in cities.

High temperatures disrupt sleep worldwide, with disproportionate impacts on older adults, women and populations in lower-income countries. A study uses climate change simulations to project future global sleep erosion and, in turn, the decline in childhood general cognitive ability and associated socioeconomic costs.

Non-optimal temperatures disproportionally affect disadvantaged populations. However, evidence remains limited on how socio-economic disparities differently shape the vulnerability and the associated burden to heat and cold across Europe. We analysed the format-homogeneous daily mortality database of the project EARLY-ADAPT (2000–2019), covering 654 contiguous regions in 32 European countries, thus representing their entire urban and rural populations, to (1) examine how socio-economic factors modified temperature–mortality associations and to (2) quantify the related burden. Regions with higher deprivation and inequality exhibited greater vulnerability to both heat and cold. In contrast, regions with higher gross domestic product per capita, life expectancy and household income showed lower vulnerability to cold but higher to heat. We estimated mortality burdens attributable to socio-economic disparities, with +301,799 temperature-related deaths linked to the inability to keep the home warm, +183,071 to population ageing (≥80 years) and +180,402 for income inequality. These findings highlight the central role of socio-economic inequalities in shaping temperature-related mortality across Europe and the urgent need for equity-focused adaptation strategies. European regions with higher levels of deprivation and inequality were associated with increased vulnerability to heat and cold, whereas regions with higher GDP and life expectancy showed lower vulnerability to cold but higher to heat.

BACKGROUND:Cold weather remains a serious health threat in the UK and elsewhere, particularly for older adults. The Winter Fuel Payment has been a key government strategy to mitigate health risks linked to cold homes in the UK, but recent policy shifts have raised questions about whether income-based eligibility criteria effectively identify those most at risk. METHODS:We analysed cold-related mortality in adults aged ≥75 across 324 local authority districts in England (2007-2019) using distributed lag non-linear models in a spatial Bayesian framework. Multivariate meta-regression was used to evaluate modification of cold effects by deprivation, income-based pension credit uptake, home energy efficiency and fuel poverty. RESULTS:Areas in the highest quartile of fuel poverty had significantly greater cold-related mortality risk than those in the lowest quartile, with a 15.3% versus 13.1% increase in mortality risk at the first compared with the 50th percentile of wintertime temperature, ie, an absolute difference of 2.2% (p<0.001). This effect was stronger than the corresponding differences for energy efficiency (1.7%, p=0.04), income as indicated by pension credit uptake (0.6%, p=0.39) and deprivation-based measures, for which differences were minimal. Overall, an estimated 17% of cold-related deaths among people aged ≥75 were attributable to fuel poverty. CONCLUSION:Fuel poverty, an indicator designed to capture both low-income and housing energy efficiency, is a stronger predictor of cold-related mortality than income (as indicated by pension credit update) or deprivation-based indicators alone. Winter energy support schemes should consider fuel poverty metrics in their targeting to more effectively reduce health risks associated with cold homes and improve equity.

Available modelling frameworks for estimating indoor temperature (T) and relative humidity (RH) for epidemiological studies remain scarce. We developed a modelling framework to assess the daily mean indoor T and RH. We monitored indoor T and RH at 1,029 homes of 978 participants from the Barcelona Life Study Cohort (BiSC), Spain (2018-2021), for one week each during the first and third trimesters of pregnancy. We applied a Deep Ensemble Machine Learning (DEML) approach to predict the daily mean indoor T and RH throughout pregnancy, which integrated predictions from three base models: Random Forest, eXtreme Gradient Boosting, and Gradient Boosting Machine. The models incorporated a comprehensive set of 56 predictor variables, including meteorological conditions, building and neighborhood characteristics, and occupants' sociodemographic and behavioral characteristics. We applied a long-term validation to assess model performance across pregnancy and a short-term validation to evaluate daily fluctuation capture. The DEML model achieved excellent performance in the short-term validation (T: R2 = 0.978, MAD = 0.312 degrees C; RH: R2 = 0.894, MAD = 1.666%), with a good performance for indoor T (R2 = 0.891, MAD = 0.717 degrees C) and a moderate performance for RH (R2 = 0.499, MAD = 3.591%) in the long-term validation. Feature importance analysis indicated that the previous one-day mean outdoor T and the same-day outdoor RH were the most influential predictors for indoor T and RH, respectively. The model reliably predicted indoor T and RH, highlighting its utility for future epidemiological studies on health impacts of indoor exposure.

Heatwaves are intensifying under climate change and have become the leading cause of weather-related mortality in Europe. Here we present a novel methodology that combines extreme event attribution methods with epidemiological models to quantify how anthropogenic climate change has altered the likelihood of extreme heat-related mortality events in 34 European countries. We find that in Southern Europe, 2022-like heat-related mortality events were, on average, 26.5× more likely relative to the pre-industrial baseline, roughly ten times the European average. The probability of such events increases further as global warming intensifies, with the greatest, nonlinear increases occurring in Southern Europe. Our analysis reveals significant regional and demographic disparities in climate vulnerability, emphasizing the need for population-specific analyses to inform effective adaptation strategies, reducing the projected health burden. Unlike other approaches, our study demonstrates that using near-real-time, publicly available mortality data enables rapid health impact event attribution analyses across large areas. A method combining extreme event attribution with epidemiological models shows that extreme heat-related mortality events in Southern Europe are 26.5 times more likely than in pre-industrial times, with regional and demographic disparities.

BACKGROUND:Intensifying heatwaves driven by climate change pose a severe and disproportionate health burden, particularly for populations undergoing rapid demographic and environmental transitions, yet globally comparable projections of future mortality under varying scenarios remain limited. METHODS:We constructed a global, grid-based, and three-stage framework covering 176 countries, integrating climate projections from 20 CMIP6 models under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Heatwaves were defined as ≥2 consecutive days with grid-specific daily mean temperatures exceeding the 95th percentile. Historical heatwave-mortality associations from 750 locations, together with future population distributions, urbanisation trajectories, and adaptation scenarios, were incorporated to estimate excess heatwave-attributable deaths during the 2030s, 2050s, and 2090s, with uncertainty quantified via Monte Carlo simulations. FINDINGS:Global heatwave-related deaths are projected to increase from 1,018,776 (95% UI: 935,188-1,106,785) in the 2000s to 5,289,925 (95% UI: 2,665,816-8,287,210), 8,814,669 (95% UI: 5,055,306-13,734,514), 13,690,238 (95% UI: 9,902,215-19,250,977), and 16,133,330 (95% UI: 11,559,920-21,300,978) in the 2090s under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Sub-Saharan Africa will suffer from the largest heatwave-related deaths in the 2090s, contributing to the proportion of approximately 20.33%-24.92%. Projected slopes are steeper under low urbanisation level, SSP3 population scenario, and no adaptation scenario. INTERPRETATION:The projected heatwave mortality burden underscores the urgent need for targeted climate adaptation, urban planning, and public health strategies. The findings reveal differential vulnerability across populations and regions, offering guidance for resource allocation to strengthen resilience in a warming world. FUNDING:National Natural Science Foundation of China (No. 42575195), China Postdoctoral Science Foundation (No. 2025M780707), and Guangdong Provincial General Colleges and Universities Innovation Team Project (Natural Science) (No. 2024KCXTD004).

BACKGROUND:We aimed to estimate the association of air pollution and term low birth weight (LBW) by maternal education and assess the distributional impact of meeting European Union and World Health Organization air pollution targets and universal tertiary maternal education on LBW cases. METHODS:We analyzed administrative data on 1 409 084 term births in Spain (2010-18) and high spatial resolution estimates of maternal particulate matter with a diameter of 2.5 micrometers or less (PM2.5) and nitrogen dioxide (NO2) exposure. Single-exposure distributed lag non-linear models were used to estimate exposure-response functions (ERF) for LBW (<2500 g) overall and by maternal education. We then applied G-computation to estimate changes in LBW cases under counterfactual scenarios: target levels of PM2.5 (10 and 5 µg/m³) and NO2 (20 and 10 µg/m³), and universal tertiary maternal education. RESULTS:A 10 µg/m³ increase in PM2.5 and NO2 was associated with 6% [95% confidence interval (CI): 0%-11%] and 1% (95% CI: 0%-3%) higher odds of LBW. Relative to tertiary education, secondary and primary education were associated with increased LBW odds [1.32 (95% CI: 1.30-1.35); 1.76 (95% CI: 1.71-1.82)]. Meeting the 10 and 5 µg/m³ PM2.5 limits would have prevented 662 (95% CI: -4 to 1271) and 2032 (95% CI: -74 to 3900) LBW cases in 2010-18. Meeting the 20 and 10 µg/m³ NO2 limits would have prevented 432 (95% CI: -16 to 848) and 938 (95% CI: -50 to 1860) LBW cases in 2010-18. Universal attainment of tertiary education would have prevented over 9200 LBW cases. The primary maternal education group showed the highest shares of LBW cases, but they also experienced the largest relative reductions under air pollution intervention scenarios. CONCLUSIONS:Expanding access to higher education may yield large reductions in the burden of LBW. Reducing air pollution exposure could also meaningfully reduce LBW burden, particularly among infants from lower educated mothers, and contribute to narrowing related health inequalities.