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ObjectivesThis study aims to estimate the short-term preventable mortality and associated economic costs of complying with the World Health Organization (WHO) air quality guidelines (AQGs) limit values for PM10 and PM2.5 in nine major Latin American cities.MethodsWe estimated city-specific PM-mortality associations using time-series regression models and calculated the attributable mortality fraction. Next, we used the value of statistical life to calculate the economic benefits of complying with the WHO AQGs limit values.ResultsIn most cities, PM concentrations exceeded the WHO AQGs limit values more than 90% of the days. PM10 was found to be associated with an average excess mortality of 1.88% with concentrations above WHO AQGs limit values, while for PM2.5 it was 1.05%. The associated annual economic costs varied widely, between US$ 19.5 million to 3,386.9 million for PM10, and US$ 196.3 million to 2,209.6 million for PM2.5.ConclusionOur findings suggest that there is an urgent need for policymakers to develop interventions to achieve sustainable air quality improvements in Latin America. Complying with the WHO AQGs limit values for PM10 and PM2.5 in Latin American cities would substantially benefits for urban populations.

Assessing the association between temperature frequency and mortality can provide insights into human adaptation to local ambient temperatures. We collected daily time-series data on mortality and temperature from 757 locations in 47 countries/regions during 1979–2020. We used a two-stage time series design to assess the association between temperature frequency and all-cause mortality. The results were pooled at the national, regional, and global levels. We observed a consistent decrease in the risk of mortality as the normalized frequency of temperature increases across the globe. The average increase in mortality risk comparing the 10th to 100th percentile of normalized frequency was 13.03% (95% CI: 12.17–13.91), with substantial regional differences (from 4.56% in Australia and New Zealand to 33.06% in South Europe). The highest increase in mortality was observed for high-income countries (13.58%, 95% CI: 12.56–14.61), followed by lower-middle-income countries (12.34%, 95% CI: 9.27–15.51). This study observed a declining risk of mortality associated with higher temperature frequency. Our findings suggest that populations can adapt to their local climate with frequent exposure, with the adapting ability varying geographically due to differences in climatic and socioeconomic characteristics.

Background: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. Objectives: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. Methods: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 μm (PM10), PM ≤ 2.5 μm (PM2.5), 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. Results: We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th 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 1st and 99th 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 PM2.5 and NO2. Conclusions: 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.

Summary: Background: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. Methods: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. Findings: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99th temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. Interpretation: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change. Funding: This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University's NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033 The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.

Background: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. Objectives: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. Methods: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. Results: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0–7 (0.9 °C). An IQR increase in inter-day TV0–7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0–7 and inter-day TV0–7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. Conclusions: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Heat- and cold-related mortality risks are highly variable across different geographies, suggesting a differential distribution of vulnerability factors between and within countries, which could partly be driven by urban-to-rural disparities. Identifying these drivers of risk is crucial to characterize local vulnerability and design tailored public health interventions to improve adaptation of populations to climate change. We aimed to assess how heat- and cold-mortality risks change across urban, peri-urban and rural areas in Switzerland and to identify and compare the factors associated with increased vulnerability within and between different area typologies. We estimated the heat- and cold-related mortality association using the case time-series design and distributed lag non-linear models over daily mean temperature and all-cause mortality series between 1990–2017 in each municipality in Switzerland. Then, through multivariate meta-regression, we derived pooled heat and cold-mortality associations by typology (i.e. urban/rural/peri-urban) and assessed potential vulnerability factors among a wealth of demographic, socioeconomic, topographic, climatic, land use and other environmental data. Urban clusters reported larger pooled heat-related mortality risk (at 99th percentile, vs. temperature of minimum mortality (MMT)) (relative risk = 1.17 (95%CI: 1.10; 1.24), vs peri-urban 1.03 (1.00; 1.06), and rural 1.03 (0.99; 1.08)), but similar cold-mortality risk (at 1st percentile, vs. MMT) (1.35 (1.28; 1.43), vs rural 1.28 (1.14; 1.44) and peri-urban 1.39 (1.27–1.53)) clusters. We found different sets of vulnerability factors explaining the differential risk patterns across typologies. In urban clusters, mainly environmental factors (i.e. PM _2.5 ) drove differences in heat-mortality association, while for peri-urban/rural clusters socio-economic variables were also important. For cold, socio-economic variables drove changes in vulnerability across all typologies, while environmental factors and ageing were other important drivers of larger vulnerability in peri-urban/rural clusters, with heterogeneity in the direction of the association. Our findings suggest that urban populations in Switzerland may be more vulnerable to heat, compared to rural locations, and different sets of vulnerability factors may drive these associations in each typology. Thus, future public health adaptation strategies should consider local and more tailored interventions rather than a one-size fits all approach.

Abstract New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature‐mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population‐weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high‐resolution GCDs (HadUK‐grid UKPOC‐9 and MeteoSwiss‐grid‐product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi‐Poisson time series regression with distributed lag nonlinear models to obtain the GCD‐ and region‐specific temperature‐mortality associations and calculated the corresponding cold‐ and heat‐related excess mortality. Although the five exposure datasets yielded different average area‐level temperature estimates, these deviations did not result in substantial variations in the temperature‐mortality association or impacts. Moreover, local population‐weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data.